text:
phylogenetic analysis of gene enrichment?
Are there any tools to do phylogenetic analysis of gene enrichment? This is, I have a list of genes from an experiment performed in several species, with a z-score that can be described as "enrichment" associated to each gene in each species. It's not gene expression, it's enrichment of a certain marker n the gene. I would like to compare these lists, that are not fully overlapping, across the phylogeny of the species, to see significant changes in the trend of enrichment at the gene level, or at the branch level. What tools could I use for this?
Species1 Z-score
Gene1    0.532
Gene2    0.531
...

Species2 Z-score
Gene1    0.51
Gene3    0.505
...

Out of interested, what is the marker you are using to score each species enrichment?

It's TF motif predictions over small windows of genomic regions.

OK, and I take it you have tried hierarchical clustering? Certainly where I would start

I forgot, before post, but here is an example of Directed Acyclic Graph (DAG) for over-representation analysis http://brainchronicle.blogspot.mx/2012/05/another-look-at-over-representation.html

Phylogenetically analyzing genes that are not present in every species may present you with some problems, but it is completely feasible to simultaneously analyze the relatedness of the species (based on your enrichment score), and the relatedness of the scores themselves.
Forgive me if this is too 'simple' an analysis, but you have not said what you have tried.
My choice of approach would be to use R (open source stats package) to generate a heatmap of your matrix of data. There are plenty of options for the method of clustering, but the defaults tend to produce quite a nice heatplot, with hierarchical cluster analysis performed on both dimensions of the data (you can specify only 1, or even none, if you prefer). I have used the following code to simulate some data to generate the below heatmap;
# generate 10x10 matrix using random data
x <- as.matrix(data.frame(rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10),rnorm(10)))
# use heatmap function on the data. "labRow" and "labCol" simply remove the labels.
heatmap(x, xlab="Genes", ylab="Species", labRow="", labCol="")

Because it is randomly generated data there are no patterns really, but if you were to stick you real data in there it would look better no doubt. (In an actual analysis you will want to leave the labels on, I was just simplifying the plot). The function can handle missing values, so you could put all the genes you want to analyze in there, even if not all species have them.
Using this method you could see the most closely related species by gene enrichment, and also which are the most closely related genes (in terms of enrichment for your TF).

From your example
Species1 Z-score
Gene1    0.532
Gene2    0.531
...

Species2 Z-score
Gene1    0.51
Gene3    0.505

You need to get a matrix for all the Z-scores from your species, like this
Genes    Species1    Species2
Gene1    0.532         0.51
Gene2    0.531         NA
Gene3    NA            0.505

And then, you can easly calculate the distance matrix for your enrichment set, to do phylogenetic analysis with R
For example
genes <- c(paste(rep("gene",10), seq(1,10,1), sep=""))
Species <- c(rep(rnorm(10, 0.5 ,0.3), 10))
Species.name <- c(paste(rep("Species", 10), seq(1,10,1), sep=""))

gene.matrix <- data.frame(Species1=Species[1:10], Species2=Species[11:20],
                          Species3=Species[21:30], Species4=Species[31:40],
                          Species5=Species[41:50], Species6=Species[51:60],
                          Species7=Species[61:70], Species8=Species[71:80],
                          Species9=Species[81:90], Species10=Species[91:100],
                          row.names=genes)

d.gene.matrix <- dist(gene.matrix, method = "euclidean")

tree <- hclust(d.gene.matrix)
plot(tree)

    > gene.matrix
         Species1   Species2   Species3   Species4   Species5   Species6   Species7
gene1  0.97128393 0.97128393 0.97128393 0.97128393 0.97128393 0.97128393 0.97128393
gene2  0.85378459 0.85378459 0.85378459 0.85378459 0.85378459 0.85378459 0.85378459
gene3  0.85152911 0.85152911 0.85152911 0.85152911 0.85152911 0.85152911 0.85152911
gene4  0.52703866 0.52703866 0.52703866 0.52703866 0.52703866 0.52703866 0.52703866
gene5  0.49145958 0.49145958 0.49145958 0.49145958 0.49145958 0.49145958 0.49145958
gene6  0.70815764 0.70815764 0.70815764 0.70815764 0.70815764 0.70815764 0.70815764
gene7  0.66739808 0.66739808 0.66739808 0.66739808 0.66739808 0.66739808 0.66739808
gene8  0.47487837 0.47487837 0.47487837 0.47487837 0.47487837 0.47487837 0.47487837
gene9  0.13635000 0.13635000 0.13635000 0.13635000 0.13635000 0.13635000 0.13635000
gene10 0.07511424 0.07511424 0.07511424 0.07511424 0.07511424 0.07511424 0.07511424
         Species8   Species9  Species10
gene1  0.97128393 0.97128393 0.97128393
gene2  0.85378459 0.85378459 0.85378459
gene3  0.85152911 0.85152911 0.85152911
gene4  0.52703866 0.52703866 0.52703866
gene5  0.49145958 0.49145958 0.49145958
gene6  0.70815764 0.70815764 0.70815764
gene7  0.66739808 0.66739808 0.66739808
gene8  0.47487837 0.47487837 0.47487837
gene9  0.13635000 0.13635000 0.13635000
gene10 0.07511424 0.07511424 0.07511424


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Combining gene expression data from two species
I currently have two sets of gene expression data. The first is a dataframe of genes identified by Annotation id CG numbers (for example "CG10005") in one column and a numerical variable of interest associated with each of those genes in the other (the important part is that the genes are identified by the CG number). The second dataset is this study from multiple species where genes are identified by "GLEANR" ID's like this one: "dsim_GLEANR_10060".
I would like to extract all of the values from this study for the D.melanogaster and D.simulans data, then link that to the Annotation ID's in the first dataset (to connect my variable of interest to the sex bias in expression for each species). The trouble I am having is connecting the orthologous genes within the second study to each other, and then connecting them to the CG identifiers in the first study.
Does anyone have any suggestions on resources which can be used to get this all to link up?

This is the FlyBase page for the example gene: Dsim\GD10095. There, you have a section "orthologs", linking to OrthoDB. So my suggestion is: Find the list of synonyms for D. simulans on FlyBase (perhaps here?), download the Drosophila section of OrthoDB, and finally find the 1:1 orthologs.

Thanks, I am looking at this now - I assume each gene has a unique FBgn and their orthologs are identified by the ODB6_OG_ID (?) and the species identified by DROME, DROSI, DROSE... taking just those three variables I can create a data frame of each ODB6_OG_ID in the first column and columns for each species giving its orthologous FBgn ID for each species of interest? But how do I "Find the 1:1 orthologs"?

Sometimes you have a strain-specific gene duplication, which you probably want to exclude to keep things simple. So you can check for each species if there's more than one gene associated with an ODB6_OG_ID, and remove those.

I got this all working after a good ol' fashioned wrestle with R today - thanks a lot for the help!

You could also use biomart for this purposes.
Click on the "ID Converter" tab in the "Tools" section (on the left).

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text:
Why does the body not recycle red blood cells?
This question is out of curiosity.
The life expectancy of a red blood cell (RBC) is approximately 3 months, and then RBCs are disposed of. Why does the body opt to build new red blood cells rather than using the existing ones? Do RBCs lose functionality/efficiency as they get older?

They are recycled, the iron and other components are broken down and then absorbed. Adaptations of the RBC prevent the same RBC being used. They lack a nucleus to make them highly efficient oxygen carriers (pack as much haemoglobin as possible). Without a nucleus and other organelles they're unable to synthesise the stuff they'd need for renewal. There's a lot of wear and tear that occurs as they're constantly flowing in tiny blood vessels and getting damaged or affected by substances in the blood.

Just one additional factor worth mentioning: the haemoglobin-oxygen interaction is a source of damaging free radicals which add to the 'wear and tear'.

RBCs do lose their functionality as they get older. In addition to the free radical damage they receive, the cells also become smaller over time which increases the effective concentration of the haemoglobin which causes other problems like hemolysis or rigidity.

I didn't know this - do you have a reference?

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What are gram negative and positive bacteria?
I've just finished a course of double antibiotics for Helicobacter pylori in my stomach.  I looked up H. pylori and found that it was a gram-negative bacterium.  I looked up gram-negative and didn't understand the definition.  I assume that if there are gram-negative bacteria then there are also gram-positive ones.  Can someone explain the terms gram-negative and gram-positive in basic, layman's terms?
Thanks,
Sachin

Just to make @yamad's answer more layman friendly, essentially Gram-positive bacteria have thicker cell walls than Gram-negative bacteria.

Why is this distinction important anyway?

It is simply one of the major ways that bacteria are categorised. The cell wall will affect what drugs can kill them for example.

@yamad is right on - Gram stain is a major way of categorizing bacteria. Its worth mentioning what the Gram stain color means.
While not failproof, the Gram stain test reflects a major division of the sorts of cells bacteria, helping to type the bacteria of interest
Gram stain reacts with the peptidogycan to create the purple color.  The peptidoglycan is a mesh of carbohydrate (sugar) chains with short peptides attached to them that gives the bacterial wall mechanical strength against osmotic changes in the environment (e.g. large concentrations changes in sugars or salts) and mechanical stresses such as shearing from current.

Gram Negative bacteria have two lipid membranes with peptidoglycan sandwiched in between them while Gram positive bacteria have a single lipid membrane with the peptidoglycan mesh surrounding the membrane, forming an outer coat to the bacteria.  There is typically 5-10 times more peptidoglycan by weight in Gram Positive bacteria.  As such these two distinct categories of Bacteria is often the first determination used to characterize a bacterium.  Again while not without some error, Gram stains reflect a significant cell physiological division in bacteria.

The Gram stain is one of a large number of techniques used to characterize bacteria. In particular, a bacterial species is usually either Gram-positive (purple when stained) or Gram-negative (pink when stained). In Gram-postive bacteria, the cell wall is thicker and has much more peptidoglycan compared to Gram-negative bacteria. The chemicals in the stain react with these molecules in the cell wall and result in the purple color. All of this information is well covered in the Wikipedia article on the subject.


text:
Proteins that are strongly overproduced in E. coli and S. cerevisiae?
I'm looking for some pointers to proteins that produce at really gigantic levels in E. coli and yeast (S. cerevisiae).  Can anyone point to some champion proteins?
Even in inclusion bodies and non functional, just cases where the yield is very high - how much of a given protein can a liter of E. coli or S. cerevisiae make?
I've seen bands on gels like this, but I've probably not seen the champions:

It would be great if you could cite and discuss the plasmid/promoter used and whether codon optimization or other such tricks made a difference.

thanks for the pointer - I was hoping to get some pointers to specific genes nearer the maximal limit though.  OSCP is promising though - if nobody has anything better than that maybe i'll go there.

@Leonardo, CMV in ecoli probably would be a bad idea ;). I've heard that typically 1/6 of the cell weight would be protein so 20% doesn't sound too crazy.

The promoter is good information - I have only worked with T7 promotor for protein production I think.

Heat shock proteins - HSP70 and HSP30.
You may also have ribosomal subunits as well.

interesting!  a reference would be appreciated?

Definitely agree. HSP70 is produced in gigantic quantities especially during recombinant protein expression in E. coli. You can get rid of HSP70 by doing a pulldown with denatured protein and ATP.

Here you go:http://www.wikigenes.org/e/gene/e/398343.html


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How to perform cell biology research without lab affiliation
Related to this question, I am wondering just generally how one can do cell biology research without being part of an already well-established University laboratory. I am not doing this myself but am just curious what the process is like for somehow getting to be one of the ones to be approved to do such research, approved to buy cells or other things like that.
The only places I know of currently that are approved are well-established Universities. That makes sense because they have good intentions and they probably have a lot of manual contracts or inspections and that sort of thing. But then at a second level of approval, there are big private companies like Genetech that probably also have approval of some sort (although maybe they "started at the beginning" by building their own cells from scratch sort of things, and so never needed approval). Then at a third layer are smaller private companies that either buy cells for research, or make their own somehow. I don't know of any examples of this but there's probably some less well known 10-20 person companies that have access to cells for research somehow, at least I would imagine. If there are not any examples of that it would be interesting to know.
But say you are either a nonprofit or a private company just starting out, and you would like to do research or provide some service that requires expressing DNA at large scales and requires a streaming supply of cells to do that. I wonder what your options are just generally (to keep this question focused not on specific companies that offer solutions to this, but on the general process). Maybe it requires you have 1 person on the team with a PhD of some sort. Or perhaps a Masters degree is acceptable. Or maybe you can get by just a Bachelors degree in Biology. Or maybe just a college degree in any major. I wonder if you can go further and, no one on the team has graduated from college (if they are young and in college), or they are older and no one went to college, they are just self-taught. So part of this question is if there is a degree requirement to being approved to buy cells (and other stuff).
So as a new company or non-profit, you start "establishing a lab" from scratch. You invest in some machines somehow. You either have some PhD's, or no one even graduated from college, but in both cases you have the same level of expertise. The part here is how you, as someone working for this "new lab", can express to some company like ATCC that sells cells, that you are affiliated with a lab doing ethical research or work for expressing DNA for some service.
Basically the question is, how a newcomer breaks into the space and can start either doing research or performing a service that requires having access to cell lines and such. What the general requirements are (such as (1), must have at least 1 PhD, (2) PhD must be affiliated with a University laboratory (i.e. they must have been a PostDoc for x years at that University, or must currently be partially employed there), and (3) you must have some sort of legal "Code of Conduct" or some guidelines for good ethics). Currently, I can't see how any new lab can be established, unless it is established as a branch/offshoot of an already existing lab.
The only example I can think of as a startup that might've been in this situation is like 23andMe, founded in April 2006 (12 years ago) by Linda Avey who only had a Bachelor's degree in Biology it looks like, and Anne Wojcicki, who also just had a Bachelor's degree in Bio but looks like they worked at some well established labs for a while (National Institutes of Health and the University of California, San Diego). I don't know if they need cells or anything, not too familiar with all that, but it seems like they probably do. "Wojcicki was married to Google co-founder Sergey Brin at the time", well that would be helpful funding-wise lol. Some helpful info:

According to Anne Wojcicki, 23andMe had been in dialogue with the FDA since 2008.[31] In 2010, the FDA notified several genetic testing companies, including 23andMe, that their genetic tests are considered medical devices and federal approval is required to market them; a similar letter was sent to Illumina, which makes the instruments and chips used by 23andMe in providing its service.[29][35][36] 23andMe first submitted applications for FDA clearance in July and September 2012.

But it's like, you need to have all these tests and results to demonstrate to regulators that this is ethical and not a health issue and whatnot. But I don't see how you can even perform those tests and get those results in the first place, since you don't have access to anything. Someone is doing lab work in private somewhere, pre-regulation. Or perhaps you have to submit proposals that need to be approved first before even embarking on initial experimental tests to get initial basic results. But if you have the funding (without needing to write grants, like 23andMe), it seems you don't need to get any approval first.

23andMe began offering direct-to-consumer genetic testing in November 2007. Customers provide a saliva testing sample that is partially single nucleotide polymorphism (SNP) genotyped and results are posted online.[13][57][58] In 2008, when the company was offering estimates of "predisposition for more than 90 traits and conditions ranging from baldness to blindness", Time magazine named the product "Invention of the Year."[10]
After the sample is received by the lab, the DNA is extracted from the saliva and amplified so that there is enough to be genotyped. The DNA is then cut into small pieces, and applied to a glass microarray chip... If the sample has a match in the microarray, the sequences will hybridize, or bind together, letting researchers know that this variant is present in the customer's genome by a fluorescent label located on the probes.

So maybe 23andMe had PhDs who did all the communication or something with the companies to get the cells for these experiments.
Also to just throw it out there, I am not really sure what "lab affiliation" means. If it means (a) you are actively employed at the lab, or (b) were employed at some point in the past, (c) for how long does it matter you were employed, and (d) if you need to have been working at that lab with a PhD, or if being an undergrad or other sort of helper counts. Not sure if clarifying that would help answer the question.
I ask because there is no place online where you can just click "S. cerevisiae, Strain A -> Add to Cart -> Checkout -> [Enter credit card info and press Buy now]" and get cells delivered to your door the next day. Something is in the way there (obviously not talking about the physical aspect of transporting the chilled cells and such). Something is going on in between an individual/new organization, and getting the cells. I'm not sure what it is (if it purely just laws, or what it is). If it is purely just laws, then that is good to know and the answer to this question is "It is purely the laws that govern this, it doesn't matter your degree or lab affiliation" is a good one sentence answer. Otherwise maybe it is some other social contracts like forming good B2B relationships over time, or knowing a friend-of-a-friend sort of thing. Or perhaps something else like degree requirements, etc..

Your answer will be very different if you want to work with cell lines or with human samples (like 23andMe). There's not a whole lot of unethical things you can do with cell lines, but human samples will have a much higher bar in terms of ethics, privacy, and medical intervention.

An answer containing the situation with the lowest bar would be the most helpful (so just with cell lines), as that would set the foundation for understanding how to handle the higher-bar situations.

I think your question is off-topic because it is not about biology in terms of SE Biology, but I am curious why you think it is not possible to buy cells and other biological supplies without some sort of approval. Obviously this relates to the laws of the country you are in — in your case the US, where I would imagine it is under state juristriction. Have you tried to buy biologicals? Presumably poisons might be under a different category, although you might regard this as the "right to bear arms".

I'm voting to close this question as off-topic because it is about US State laws.

No but the linked question I proposed at the top was closed and the comments said basically that you need approval.

I am not wondering about state laws, that is the details of how to actually do stuff. I am wondering about the general process instead of the specific details. After knowing the general process, then I would be prepared to know what to consider in terms of laws, and could ask on law.stackexchange.com. Just stating as one of the steps "Find out the regulatory laws" would be enough legal stuff for me.

This question is on topic: "questions about techniques in a biological or biochemical laboratory".

I think there are just too many different questions here and as @David pointed out it isn't really about biology but rather a legal question. You aren't asking about techniques from a biology perspective, at best you are asking about regulatory compliance for which the answer is always going to be "it depends" and "we can't offer legal advice." In addition, your question covers a whole scope from regulatory approval for medical device marketing to experimental biology.

Ah, maybe this question simply boils down to "How to build a new lab", in which case this and this about Biosafety Levels and permits is pretty much all you need to know. So it doesn't seem to require PhDs or anything so far.

@LancePollard I am thinking you need to know about your closest available University that offers Cooperative Extension Services!  Yes!  I tried to read through to see if anyone picked up on this!  Your best bet is to go find your closest Cooperative Extension Service!  Oh my.  they offer Joe Blow classes to become a Master Gardener, a Master Composter, a Master Food Preserver as well as Master pruner!  They are the ones to get to know like NOW!  They also have (used to be free) soil testing.  They might allow you to use their labs or direct their techs for studies, perhaps if you landed grants

@stormy what you wrote sounds a bit like spam so I can't tell if you're serious. Maybe if you wouldn't mind posting a link to an example or something perhaps.

The resource I am talking about is a State's University (one of them) Cooperative Extension Service.  It is almost FREE.  This extension service is non profit.  I took their Master Gardener Course 3 times, Priceless.  They KNOW your locality, the zones, the soils the special differences for your locality...to not know about this service is a shame.  Check it out.  Spam?  Are you kidding me?  Please, let me know....

One needs to be part of the University to do purchase orders within the University.  That makes the most sense.  Otherwise someone outside the realm of the University needs to learn about University outreach programs such as Vocational Education and the Cooperative Extension Service or be privately funded.

In general, I think that degrees would not matter. PhD is not a license (compared to licensed medical doctor) but a scientific degree, reflecting some amount of education and achievement.
There are many governmental regulations that apply to organization that seeks to work with human tissues, import/export biological samples, order regulated substances et cetera. There are review papers, for example "Guidelines for the use of cell lines in biomedical research"
Another layer of regulations, that universities are particularly prone to, are ethical guidelines established by funding sources. For example, NIH have specific guidelines for work with human subjects and specimens. You will have to pay attention and comply, if you want to get their funding. Universities have dedicated groups of people who are in charge of making sure that these policies are followed, you don't want your organization to fall out of favor with funding agencies.
All together, it seems that establishment of private lab is logistics problem. Compared to research universities, you lack legal and operational teams that know all the caveats of the regulations, as well as just plain handling of materials. You need Purchase Orders most of the time, not credit card, to buy something from ThermoFisher or Sigma-Aldrich, and that is done via purchasing departments at universities.

Thank you, this is nice. This answered pretty much everything, thank you. I have never heard of Purchase Orders, good to know.

I'd also like to point out on that very note @LancePollard that setting up an account with a scientific vendor often requires a commercial credit application, because POs are executed on a net-15 or net-30 days regimen, i.e. they don't take your money immediately, so you need to be credit-worthy.

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text:
How a Name is Selected for Binomial Nomenclature
I understand the gist of how to construct a name using the Binomial Nomenclature, but I don't understand how to select a unique name.
My contrived example comes from looking at this:

acaulis: stemless, e.g. silver thistle, Carlina acaulis.

So assuming the naming is <Genus> <Species>, then within the genus say we have 20 species already, which is fairly modest given this description of genus size:

The number of species in genera varies considerably among taxonomic groups. For instance, among (non-avian) reptiles, which have about 1180 genera, the most (>300) have only 1 species, ~360 have between 2 and 4 species, 260 have 5-10 species, ~200 have 11-50 species, and only 27 genera have more than 50 species (see figure). However, some insect genera such as the bee genera Lasioglossum and Andrena have over 1000 species each. The largest flowering plant genus, Astragalus, contains over 3,000 species.

Looking at the Astragalus genus gives some insight to the potential naming conflicts.
But say we have our 20 species in our custom genus. Our genus is called Foo and our species are (translated into Latin):
Yellow
Green
Blue
Shiny
Spotted
...

Now say we discover a new species and the prominent features are that it is both Shiny and Yellow, whereas those previously defined species are only either Shiny or Yellow, not both. So now we have one that is both, and we are having a hard time finding any other distinguishing factors.
One approach would be to call it the Double (diplo-) species, since it is both Yellow and Shiny. So perhaps we add to our list (in Latin maybe "diplopicta")
Foo DualColor (or Foo Diplopicta)

But wait! We already have used this technique (let's say). We look further in the original list and yep it's already there.
Yellow
Green
Blue
Shiny
Spotted
...
DualColor
...

So we can't use that technique. So maybe we go to the location, say it is northern:
Foo NorthernLocation

But wait! We already used that technique too!
Yellow
Green
Blue
Shiny
Spotted
...
DualColor
...
NorthernLocation
...

So now maybe we just try using another feature that we haven't used yet in any of the other species. Maybe this thing also is slightly larger than most of the other ones, and we haven't used Large as a property.
So we add (in Latin):
Foo LargeSize

Then we find some more species and we keep having to try to come up with new ways to get unique names. Maybe we try other things like:

Specific continent.
A feature that hasn't been used yet.
The discoverers name.
etc.

Already it's kind of brittle feeling.
Now let's say we discover a new species in the genus again. But this one is really really yellow. Way more yellow than the previous one we called yellow. And that is it's only distinguishing feature. I would like to know what is done in this situation.
I would like to know, generally, how this process like described above is handled in practice in the real world.
So we have this new yellow thing. Now we want to rename the old species and use Yellow for this one, and come up with something better for the old one. Not a problem if this information hasn't been shared yet. But if it's already been shared all over the world then you can't really change it, at least not with a long and drawn out, carefully managed process.
So we're stuck with the less than ideal name for our new "really really yellow" thing, and we just end up calling it:
Foo CoreyDiscoverer

But at this point I feel like might as well just give it a number ID since there's not really any meaningful connection (though history perhaps is a good enough connection).
Basically I'm wondering how good names are created for things using the Binomial Nomenclature, and how naming conflicts (or the desire to change names) are handled. The example above outlines a scenario that one might encounter when trying to uniquely name species within a genus, and I am wondering how it is handled in practice.
As an example, from here it reads:

If on the other hand the taxon appears never to have been named at all, then the scientist or another qualified expert picks a type specimen and publishes a new name and an official description.

But it doesn't explain how this works, the issues they had to consider as outlined above.

Your question covers a whole field of research, taxonomy, and the answer to the complexity of the naming process and how conflicts are resolved is the subject of very strict and very detailed rules. For example, the nomenclatural treatment of animals is governed by the International Code of Zoological Nomenclature, while the nomenclature of plants, algae and fungi is governed by the International Code of Nomenclature for algae, fungi and plants (paradoxically, fungi are actually more closely related to animals, but however).
These codes have a series of rules governing the ways that new names can be coined, how new names should be considered against old or preserved names, what constitutes a synonymous name, and hundreds of other little things (for example, the Shenzhen code, the most recently ratified code of the ICN, is very, very long).
Some trivia, which might give you some idea of the conflicts which are handled by the code: under the ICZN, tautonyms, which are species names where both the genus name and species epithet are the same (e.g. Vulpes vulpes, the red fox) are allowed, whereas under the ICN, they are not allowed. Species from separate codes can share the same name (see for example the answers to this question), and two species from different genera governed by the same code can share the same species epithet - it is the binomial combination which must be unique.
I am not kidding when I say the rules are really, really detailed, and the minutiae is too much to get into here. If you read the respective codes, you will get some feeling for the rules which are applied.
In regards to the other part of your question, choosing an appropriate name: this is generally at the discretion of the publishing author (unless the name is invalid under the code, then another author may step in to dispute it or correct it). These can come from all sorts of things, ranging from utterly boring and descriptive to pretty funny and facetious. For example, Han is a monotypic genus of fossil trilobite, and having only one member, its sole species is Han solo.
I suspect the reason that most materials don't discuss how this process really works is because it is really, really complicated and often pretty dry. You'll see plenty of examples of new names being coined in journals like Taxon. But doing taxonomy is often conceived as not very glamorous, so doesn't receive that much attention, even though it underpins most comparative fields like ecology and evolution.
As a final note, the reasons that a species will be included in a given genus, or split into its own genus, or several genera will be lumped together into one large genus, are more murky, and related to phylogeny, morphology, final size, etc. These decisions are often also left up to the discretion of the author, unless of course they conflict with the code.

I understand that the rules are detailed. I am more wondering though how you select a good name, not a correct one. It seems they aren't much concerned with "good" names.

@LancePollard what is good? Does it mean a name evocative of appearance, or a name designed to help you remember the system? Does it maximise the stability of the nomenclatural system or help it to reflect more natural groupings? These are all valid questions, and they've been asked as far back as Caesalpinus

Lol yeah, it is a design decision. I guess a good name would be (a) easy to remember and (b) bring up vivid mental imagery.

@LancePollard all well and good until you arrive at some plant taxa that are near identical, or something even more cryptic like red algae or bryozoans.

Exactly! That's what I was wondering about :)

As ever in biology, there are no easy answers :P

@LancePollard Unfortunately, reliably coming up with good names is an unsolved problem, not just in biology, but in general.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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High-res / high quality, public domain cell / bacteria images on the web for download
Wondering if there are any high quality, high res images of eukaryotic cells or bacteria on the web available for download (public domain). I found some illustrations which are public domain, they look nice, but they are illustrations. I would like to find SEM electron micrograph images or things of that nature, microscope images in the public domain.
Here is an SEM image that is somewhat acceptable, though it has the legend built into the image and isn't colorized (colorization would be a bonus). Here is a colorized image.
This is more the quality I am looking for.
This is decent, but it's not public domain.
These are great!
I wish some of these were public domain.

What do you want to do with them? Is it commercial use as suggested by your attitude to a CC image? Nobody ca stop you downloading for private use unless they are watermarked.

I want to give them away and let others sell them

Then — and in any case — this doesn’t appear to be a question about biology in the terms of SE Biology, I’m afraid.


text:
Where to look up animal facts concisely
Googling leads to results such as this:

DIET
  Eagles primarily eat fish, carrion, smaller birds and rodents. Eagles are also known to prey on large birds and large fish.
POPULATION
  Bald eagle numbers in the U.S. were estimated to be between 300,000-500,000 in the 1700s. Numbers were once as low as 500 nesting pairs in the lower 48 states. Bald eagle numbers have rebounded since and now the lower 48 states boast over 5,000 nesting pairs. There are a total of about 70,000 bald eagles in the whole of North America (Including Alaska and Canada).
RANGE
  Bald eagles live near bodies of water in Canada and Alaska, and in scattered locations all throughout the lower 48 states and Mexico.

I would like to find something like this but with more detail, perhaps scholarly papers or such like that, like you might find on a synopsis/summary article for a specific protein. Wondering if anything like this exists.
Examples of "facts" I would like to look up:

food sources
habitat
range
color
sound
population size
lifespan range

Stuff you see like this has few if any citations where they get the info from.

I'd write a program that can query google for complex search terms and return the related numbers, colors, phrases and paragraphs for all 10,000 most common animal species. Then simply press enter and the program could add about 100 species to the database every hour, hammering google.

@com.prehensible — Gosh! Sounds really easy. You do lot of this sort of thing?

It's called parsing. It would take literally a week to have a draft version going. I'm not very good at it, I run unity3D which does webURL queries and any code you want from it, it returns text and you just have to use string commands to search, concatenate, divide substrings. I did something like that 4-5 years ago, which builds animated 3D phylogeny trees using google image search.

@com.prehensible — you need to include the @ handle to alert anyone other than the poster to a comment. This is obviously not the place to discuss computational methods, but parsing free text successfully is a complex task, which I would be surprised to see performed with a gaming engine. And remember that Wikipedia entries are compiled by humans with at least some expertise. Who is going to tell whether pressing “enter” produces garbage or not?


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Specific enzyme for C. elegans
We are looking for an enzyme that appears in C. elegans but isn't common for: human, Drosophila or mouse.
We need it for a little research project, thanks for your help!

why enzyme? if its any enzyme, why not any gene? loosening up in this regard might make it easier.

what is your actual question?

What level of similarity would be acceptable? What do you mean by "isn't common"? What exactly do you want to do?

Do you just need a unique protein/DNA sequence, and how unique and how long does it need to be? What exactly is the aim of your project? A common problem is that protein/enzyme names may not be identical between species, but their functional domains and/or sequences could very well be, since many processes of life are conserved from one species to the next.

This question would fly rather well if you asked 'how can i find genes that are unique for C elegans?'  Is that what you want to know?

One way to approach this is to use one of the protein database clusterings available.
Researchers have taken huge protein databases, like UniProt, which basically catalog all known protein sequences regardless of species and clustered the proteins by sequence. The results provide many interesting insights about protein families, but more importantly they are well-fitted for your problem. A cluster would be a set of sequences that are similar to each other but are relatively different from all other known proteins. So, essentially you would be interested in a cluster that is only has c elegans proteins.
I went ahead and used ProtoNet, which is one such tool, and searched for such a c elegans cluster. I found two potential clusters: 4375747 and 4430980, which have mainly c elegans proteins.
Disclaimer: I have been involved in the past in the development of ProtoNet.

You might explore Li et al (2004) "Comparative genomics identifies a flagellar and basal body proteome that includes the BBS5 human disease gene" Cell 117: 541-552.  (Pubmed Abstract).
Largely the authors focused on comparisons of Arabidopsis, Chlamydomonas and Human genomes, but they did also include C. elegans for comparisons with at least Chlamydomonas (Summarized in Table 1).  Even if they do not give you exactly what you need, you could apply their methods for your particular project.


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For the human head, which direction is anterior, and which direction is ventral?
I read the wikipedia entry and I am sort of confused.
In dog, the nose is toward the front. That's anterior. So I conclude that human nose is anterior.
In dog, the head is on the back. So that's dorsal. So I concluded that humans' top head is dorsal.
Yet that's not how things seem to work on anatomy.
We call humans' top head anterior. We also call human nose direction as ventral.
How could that be?
The whole system of anterior, dorsal, ventral, posterior is there so we can see humans like we see dogs (at least anatomically).
Yet it changes again.
So which one is right?
Let me put it this way
Dog's chin is ventral from the eye
In humans, is humans' chin ventral from the eye too? or posterior?
What about the nose? Dog's nose is it's anterior most organ.
In humans, is the nose anterior too?
I mean, if we're going to have different terms for humans and dogs, might as well use words like up, down, front, back right?

It's simple - anterior = ventral and posterior = dorsal for humans.

I thought anterior posterior axis are always perpendicular to ventral dorsal axis on any area of interests?

These terms are determined for "horizontal" animals.

In other word, for humans the nose is anterior? That means the chin is dorsal then. We just need to put humans into horizontal position?

Humans are are upright in their anatomical position - fig. 1 - from which all directions and terminology stems.

Figure 1: Anatomical Position
Because of this, anterior is normally the same direction as ventral and posterior normally the same as dorsal - fig. 2.

Figure 2: Normal directions in humans
Cranial anatomy is a special case, however, as the entire axis of the body bends round during embryonic development as seen in fig. 3.

Figure 3: Bending of the developmental axis
This leads to the cranium being a little odd, where dorsal is equivalent to superior and ventral to anterior in this area of the body only

Figure 4: Resultant difference in neuroanatomy conventions
However, for convenience, anterior and posterior retain their original directions even in this area.  Therefore you could eliminate a large amount of your difficulties by just using these terms instead for most of the body.

To answer your specific questions:

So I conclude that human nose is anterior

Yes

So I concluded that humans' top head is dorsal. Yet ...We call humans' top head anterior

The top of the head is technically dorsal, however in practice would never really be referred to as such, instead being superior.

In humans, is humans' chin ventral from the eye too? or posterior?

The human chin is both inferior to the eye (looking straight at the face in the coronal plane) and anterior to the eye (but only marginally).  It's more obvious if we look at the tip of the nose instead, which again is both inferior and anterior to the eye.

In humans, is the nose anterior too?

Yes, the nose is anterior.

Is the nose ventral? So top of head is not anterior.

So that means dogs will be different than humans then?

No, the top of the head is superior not anterior and yes, in most animals other than humans the directions will be different as the majority don't walk upright so dorsal wont be the same as posterior and ventral wont be in the same direction as anterior.


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Which range are the Therapeutic Indices of Currently-Prescribed Benzodiazepines in?
A compound's therapeutic index is defined as:
$$TI = \frac{LD_{50}}{ED_{50}}$$
What range are the therapeutic indices of benzodiazepines in? For the method of administration I would prefer intravenous as with it one can estimate the therapeutic indices via other routes. Of course for humans it is difficult to find LD50's but a rat/mice LD50 will suffice provided the ED50 is for the same respective species. Such benzodiazepines I am interested in are (Although I will accept your answer if you just give me an estimate of the therapeutic indices of the drugs in bold, the others are just icing on the cake):

Alprazolam
Brotizolam
Clonazepam
Clorazepate
Diazepam
Estazolam
Flurazepam
Lorazepam
Lormetazepam
Midazolam
Nitrazepam
Temazepam

A first pass answer is 662-4342.
The Therapeutic index is calculated from rat tolerances; LD50 is a rare number to see for human beings(!).  The toxic dose of a compound can vary widely over a class of compounds as well as does the Effective Dose (ED) midpoint (ED50).
But I found this book reference:

Benzodiazepines have a wide margin of safety based on experimental studies in animals.  In the rat for example, the lethal dose of alprazolam is 331-2171 mg/kg. The effective therapeutic dose for alprazolam is 0.5 mg/kg which results in a therapeutic ratio of ... 662-4342.

The page goes on to say, at rather great length, that human evidence is that despite the fact that this is a popular class of drugs to try to kill yourself with, there are relatively few human deaths, which is pretty ultimate a judge for toxicity, though you could look for FDA warnings on the class of drugs.
I would bet that you can find relatively toxic benzodiazepines, but for the ones that pass screening they seem pretty benign as a class.  There are other issues with these drugs rather than mere toxicity - they are quite addictive, so therapeutic index is not an ultimate judge of the adverse effects of a drug.
BTW taken literally, this is a hard question you ask.  If you are expecting a compiled list of all such drugs, cross referenced to their Therapeutic index, that is really more like the work for a paper rather than 25 points of stackexchange karma IMHO.  On the other hand maybe someone has this information at their fingertips...

Is the effective dose of 0.5mg/kg for humans or rats? In order for a therapeutic index to be a fair estimate both the lethal and effective doses have to be for the one species.

Yeah I know of the therapeutic window but the problem is that we know more about therapeutic indices for other drugs so it's a more useful comparison for me.

That information would have to be dug up through pharmacology texts or the literature.  Maybe someone could know that off hand and post, but you need to name specific drugs... there could be dozens of drugs in the class.  That's asking a lot.


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Is there a Pharmacology Textbook that Satisfies the Conditions listed in the Body of this Question?
The conditions are:

As extensive and explanatory as Goodman and Gilman's The Pharmacological Basis of Therapeutics, Twelfth Edition
With additional extensive and thoroughly explanatory information on drugs (e.g. flupirtine, piracetam, nefopam, etc.) that are used elsewhere in the developed/semi-developed (like Russia or China) world (e.g. European countries) but not in the US.
Additional information about the medically recognised (in some of the world at least) herbs cannabis sativa and hypericum perforatum (St. John's wort; recognised in Germany).

If there is no such book then the European (or a European, like for instance the British equivalent. So long as said equivalent comes in English) equivalent of Goodman and Gilman's will be accepted.

We're encouraged to use Rang & Dale's pharmacology but I don't know if it will go into enough detail for you.  You might also want to try and get your hands on a BNF for the clinical side of pharmacology if you're interested in UK practices.

@BrentonHorne: If you found the book you are searching for do tell us.

@RoryM : If you convert your comment into an answer this question may be saved from deletion.

A title called Essentials of Medical Pharmacology fulfills these criteria and is quite popular in India.
Reference to the current edition:
Tripathi KD. Essentials of medical pharmacology. 8th ed. New Delhi: Jaypee. 2019; 1064 p.


text:
How might IVF (and related technologies) alter epigenetic marks?
I was reading up on KCNQ1, which encodes a voltage-gated potassium channel, and I discovered that it happens to be only maternally expressed. This is regulated by KCNQ1OT1, a non-coding RNA, which is also epigenetically regulated (expressed only paternally). Mutations in KCNQ1OT1 are associated with Beckwith-Wiedemann Syndrome (BWS).
Further reading led to the discovery that there are ART-related (assisted reproductive technology) cases of BWS due to loss of methylation at KCNQ1.
However, this article found epigenetic stability of KCNQ1OT1 methylation in cultured human embryonic stem cells, which leads me to think that KCNQ1 might also have been properly methylated.
So what exactly are assisted reproductive technologies doing that can disrupt inheritance of epigenetic marks (that culturing hESCs doesn't do)? (Is this understood for any gene?)

I recently asked a professor who works on stem cells about this, and he says it's probably an isolated case, and maybe even an experimental artifact.  I'd be interested to hear if anyone else thinks of an alternative explanation.

I was at a talk last year where some geneticists were starting to look at the effect of IVF techniques on genetic issues.  Because of the work being done and the inclinations of the clients involved, this has not been studied very much.  One presumes that since zygotes are still used, there will not be much epigenetic effects due to methylation patterns - its the same cell stocks being used in vitro and in vivo.
There may be an effect on genetics because the natural selection process.  Spermatogenesis and oogenesis is a highly selective process; only a small fraction of the ova generated by the ovaries ever mature and a large percentage of sperm generated are not motile or have other irregularities.  During fertilization, sperm competition obviously throws out all but one in 250 million.  It also appears that there are processes in the fallopian tubes that can store the sperm for several (up to 5) days before fertilization.
So while its not strongly established one can see how various IVF processes vary from in vivo fertilization.  This could have an impact on epigenetic factors, although different sperm vary genetically due to Meiosis and this would be a big source of genetic variation in the outcome.


text:
How does MEME compute the background frequency of nucleotides?
I am trying to calculate a log-odds matrix for MAST input, from a position-specific probability matrix for the motif in which I am interested.
I would like to know how MEME estimates the background frequency of nucleotides, as it does the conversion from position-specific probability matrices to log-odds matrices when you choose to run MAST on MEME output.  Is it simply counting frequencies in the sequences supplied, or is there some sort of modeling going on to correct for sample size and whatnot?
EDIT: Another possibility that occurred to me is that MAST is capable of converting position-specific matrices to log-odds matrices.  I'd appreciate it if someone could clarify this point for me (and I'm still interested in how the background frequencies are calculated).  Also, I am specifically looking for answers with links to supporting documentation.
EDIT 2 (05/07/13): Alexander has answered the original question.  Does anyone have an answer to the first edit (re: MAST)?
EDIT 3: MAST doesn't like PSPMs; it will accept the job but crash.

I am not sure about the exact algorithm but the wikipedia page on MEME, briefly explains the algorithm and how the weights are computed. You can refer to the original paper; they must have explained it in the supplementary info.

At the MEME server page, there's a link to upload a customized background markov model (using the command line interface, this is the -bfile option).  From there, there's a link to the MEME Man Page.  Under "Objective Function", it specifies:

The background model is an n-order Markov model. By default, it is a 0-order model consisting of the frequencies of the letters in the training set.

So yes, it's basically the simplest possible correction: no accounting for pairwise frequencies, complements, motif width, etc.  I expect this is because MEME can be applied to essentially any dataset, such as phage display bindings from a "truly" random set of short oligos. In which case making higher order assumptions about the pairwise independence would be detrimental.
Below that, I think it answers your question about the total log-odds calculation:

The E-value reported by MEME is actually an approximation of the E-value of the log likelihood ratio. (An approximation is used because it is far more efficient to compute.) The approximation is based on the fact that the log likelihood ratio of a motif is the sum of the log likelihood ratios of each column of the motif. Instead of computing the statistical significance of this sum (its p-value), MEME computes the p-value of each column and then computes the significance of their product. Although not identical to the significance of the log likelihood ratio, this easier to compute objective function works very similarly in practice.

Thank you for the clarification re: MEME. Do you know if MAST also does the same computation? I know it works with log-odds matrices, but I am interested in whether it also can accept position-specific matrices.

In the couple of instances that I've used MEME, I found it sorely lacking in documentation. It seemed to make the assumption that the user was already pretty expertly trained in the field. My impression is that it should be able to handle a pretty sophisticated Markov model, but I don't know how you would construct it. I tend to work at the opposite end of the comp bio spectrum. :)


text:
What is the biological mechanism underlying caffeine intolerance? (CYP1A2 or other?)
As far as I can tell, caffeine metabolism occurs primarily via the CYP1A2 enzyme. I am curious as to whether mutations in the CYP1A2 gene are associated with caffeine intolerance.  Some site that is not necessarily reputable suggested that caffeine intolerance is due to absence of the enzyme to metabolize caffeine. I am having difficulty finding evidence either supporting or contradicting this claim.
Does anyone know if there is evidence that suggests mutations in CYP1A2 (and therefore inability to properly metabolize caffeine) are associated with caffeine intolerance, or if there is another proposed mechanism for caffeine intolerance?

Yesterday I learned about this cool database linker site called biograph.be, where you can type in a gene and suspected "disease" or condition and it will generate a map showing how they've been associated in literature. Here's a start: http://biograph.be/concept/graph/C0006644/C1332826

Unfortunately, neither 'caffeine allergy' nor 'caffeine intolerance' are recognized search terms. But that is a cool site. Thanks for the link.

Yes, that links to the association between caffeine and CYP2A1 - but all of the papers that come up seem to be related to pharmacological inhibition of the enzyme, which I already know is important for caffeine metabolism...I'm interested in mutations in the gene.

I have found that caffeine is mostly metabolized over CYP1A2 (as we know), but also over CYP1A1, CYP2E1 and CYP3A4. The question is how much the individual can cope with this alternate pathways if he is a CYP1A2 poor metabolizer. [1]
Secondly I found in my pharmaceutics textbook that CYP2A1 activity determination is indicated due to undesirable side effects to caffeine and theophyllin.[2]
UPDATE: 19.03.2013 12:30 GMT+1
@dd3: To clarify the second statement: I used the approach that theophyllin and caffeine are similar xanthin derivates. Since theophyllin is used as therapeutic drug in respiratory diseases (COPD etc.), I thought that scientific interest would be greater. And yes CYP1A2 plays an important role in both theophyllin tolerance and intollerance.
I found some new sources:
At first a study with CYP1A2 knock-out mice, which shows that the elimination of theophyllin takes 4-times longer in CYP1A2(-/-)mice. And they also assume that the same behaviour is also applicable to caffeine. [3]
Also there are two clinical studies by Japanese and Turkish scientists. The Japanese conclude, that theophyllin should be used with care in CYP1A2 poor metabolizer (even in haplotype poor metabolizer), since theophyllin has a narrow therapeutic range.[4] But the Turkish scientist assume that according to their findings, theophyllin is also metabolized over alternative pathways such as CYP2A13, CYP1A1, CYP2E1, CYP2D6 and CYP3A4. And according to this the genetic status of CYP1A2 is not as important as expected. [5]
Conclusion:
Assuming that theophyllin and caffeine are metabolized similarly, you can conclude that a mutation in CYP1A2 would lead to caffeine intolerance. In my experience people with caffeine intolerance describe severe nervousness after drinking a cup of coffee. Fatal cases I know were due to high consumption of energy drinks in children without or at least not known caffeine intolerance.

Sources

[1] http://informahealthcare.com/doi/abs/10.1081/DMR-120001392
[2] german source: http://www.medizinische-genetik.de/index.php?id=2642
[3] Derkenne S, Theophylline pharmacokinetics in mice: http://www.ncbi.nlm.nih.gov/pubmed/15970798
[4] Obase Y, Polymorphisms in the CYP1A2 gene and theophylline metabolism in patients with asthma. http://www.ncbi.nlm.nih.gov/pubmed/12732846
[5] Ahmet U, The effect of CYP1A2 gene polymorphisms on Theophylline metabolism and chronic obstructive pulmonary disease in Turkish patients http://www.jbmb.or.kr

Further Reading:

Xanthines as therapeutic drugs: http://web.carteret.edu/keoughp/LFreshwater/PHARM/NOTES/Xanthines.htm

Could you clarify your second statement? I'm not sure what you mean.  Google translate of the second page seems to indicate that mutations of CYP1A2 are associated with both caffeine tolerance and intolerance -- is this correct?


text:
What is the significance and method behind Ramachandran plots?
My PI showed a Ramachandran plot in class today with minimal explanation, but I'm interested in finding out more. I understand that the Ramachandran plot shows the relation between the omega phi and psi angleson either side of an amino acid alpha-carbon, but there are a few further points I'm confused about:
a.) What do these angles describe? Are they just dihedral angles that show translation around the bond-axis?
b.) Why are these angles important beyond the scope of identifying a secondary structure? Can they be used instead to identify the amino acid components, or only higher level structural units?
c.) What kind of instrument is used to collect the data and how are angles on either side of a single alpha-carbon correlated?

Proteopedia has a nice 3D interactive visualization of the φ/ψ angles: https://proteopedia.org/wiki/index.php/Tutorial:Ramachandran_principle_and_phi_psi_angles

Ramachandran plots show the relationship between the phi and psi angles of a protein referring to dihedral angles between the N and the C-alpha and the C-alpha and the C-beta. As an aside, the omega angle between the C-beta and the N tends to be fixed due to pi-pi interactions.
Dihedral Angles

There are limits to possible distributions of phi and psi angles due to steric clashes between the side chains. Furthermore other limitations from higher order structure will result in the adoption of defined phi-psi angles. Using data from solved crystal structures, it can be seen that the dihedral angles will adopt specific conformations in a protein.
RAMACHANDRAN PLOT from Lovell et al.

Furthermore, it can be noted that some of these conformations relate to specific secondary structures. As seen above, peptides in alpha-helices and beta-sheets adopt a even more limited set of phi-psi angles. Certain amino acids like glycine and proline, which differ from from canonical amino acids have an unique Ramachandran plot.
The angles from a Ramachandran plot are useful not only for determining a amino acids' role in secondary structure but can also be used to verify the solution to a crystal structure. Furthermore, it assists with constraining structure prediction simulations and helps with defining energy functions.


text:
Downloadable worldwide database of disease statistics?
I am looking for a downloadable database of disease statistics. I have emailed the good folks over at HealthMap, but they haven't gotten back to me yet.
As far as I can tell, their data relevant to my project is gathered from the World Health Organisation, ProMED Mail, GeoSentinel, Google News, Moreover, Baidu and SOSO.
I can scrape the data from each of these sites and aggregate it in the same way HealthMap has, but that is a large project in and of itself, and I only have a couple of months for this not-for-profit project.
Do you know of a downloadable worldwide database of disease statistics?

I took a quick peek and HealthMap and their JavaScripts are publicly viewable.  As such, I believe cross site scripting would be quite feasible.  In other words, call their JavaScripts from a page you develop on your server to create a feed of the data you want.
In this way, minimal effort on your part could leverage their data scraping efforts.  If you're adding your own data then you're basically doing a Mashup.
That said, my concern with doing this is potentially violating their copyright.  I would email them saying if their database is not available then you wish to use cross site scripting to access this data for your project, and unless they let you know otherwise by (specific date) you will assume this is acceptable.
I'm not a lawyer, so use this advice at your own risk.  =)

In general it's always better to politely ask and wait for a reply. Cross-site scripting means you are using their bandwidth so you should only do that if you have permission.


text:
Software for counting fly eggs
Is there any software that could be used to rapidly (quicker than humans) count the eggs laid by Drosophila on a substrate by placing them under a microscope with a camera attached? The eggs are laid on the surface of the food and have a fairly uniform shape - we regularly have to count the number of eggs in >200 vials, which can take a over 4-5 hours per 100 vials.
I wonder if there is some software which could be linked to a microscope with mounted camera connected to a computer, the software could then count from the live feed or a quickly taken photograph. It wouldn't have to be perfect but as long as it could be as accurate as humans (which is surprisingly low from our experience - we count up to a set amount then remove the rest, e.g. if I was aiming to leave 180 eggs I would be quite happy to get anywhere between 150-200 eggs). It would be using a stereo-microscope (aka dissection microscope) with a mounted camera.
The surface of the food with eggs looks something like this ->

purely for illustration, taken with iPhone - real images on microscope would be able to get closer (food surface could fill screen) and have more uniform lighting to give better contrast (this was taken to show in a talk so I wanted pretty rather than practical). The bottom two quarters of the food in this picture would be similar to the real result, just much closer...

Matlab allows image analysis like this. Check the matlab image analysis toolbox.

@WYSIWYG I'll give it a look, do you know if it would be able to do this live? (i.e. put the vial under the scope, focus it, click a button & get a count, then I remove some eggs & put it back under for a recount?)

I am sure it can be configured for a direct data acquisition and counting. I remember someone telling me about counting fluorescent puncta in cells, under confocal microscope, using matlab.
That is, however, beyond the scope of my existent skills and you can talk to any instrumentation engineer in your university

another software called LabView by national instruments can also do such a job. It's not that difficult to use.

here's another image analysis package that may do what you want http://fiji.sc/Fiji

ImageJ is a multi platform piece of software that has a cell counter module that might be of some use, and hey its free! Its easy to use and so ludicrously crude that it is very  versatile. I remember using it in undergrad to count cells under the microscope automatically after a few image contrast tweaks. I don't see why this couldn't be reapplied to count eggs.
Download: http://rsb.info.nih.gov/ij/download.html
Cell Counter documentation: http://imagej.nih.gov/ij/plugins/cell-counter.html

excellent, I'll try to find time to try it out in the new year and let you know how I get on!

Mathematica, if your institution has it as a bulk license option that you can get for free, is also a decent competitor to ImageJ for image analysis, assuming you do not know either program. A bonus is that you can hop over to Mathematica SE if you run into problems. I have used it for fluorescent microscopy counting and imaging as seen in http://mathematica.stackexchange.com/questions/29844/counting-elements-which-are-inside-another-element-on-a-different-colour-channel


text:
Biological key file format
I am in the process of creating biological key software tool for use on android devices. I would like to know if there are any established file formats for storing biological key data.
Thanks

Could you give us some more details about what you're looking for? Maybe I'm just not familiar with your terminology, but I'm not sure what biological key data is. I work in Bioinformatics and have done some Android development, so I might be able to help you!

Dichotomous key?

Yes, A dichotomous key. apologies for not being more specific.

@user521469 The Wikipedia page here points to software which may be a source of file format definitions.

I searched a bit and could not find any such format, but I am not a specialist in taxonomy.
From what I understand, the structure you want is that of either a tree or a DAG (Directed Acyclic Graph). Both are straightforward to store in a variety of formats.
One possibility is to use a format similar to other biological data that has a similar data structure. For example, Gene Ontology is a widely used dataset that has the structure of a DAG and has a number of formats including XML listing the parents and additional data of each node in the graph. See here for their formats.

If you mean some thing like .doc .txt .rar or etc. I think there is no special bioinformatics file formats like that, for example NCBI, EMBL, Expasy and others use this common formats in transfering sequence data. BUT there is some thing called file format for introducing data to this data banks for example FASTA file format:

>gi|5524211|gb|AAD44166.1| cytochrome b [Elephas maximus maximus]
  LCLYTHIGRNIYYGSYLYSETWNTGIMLLLITMATAFMGYVLPWGQMSFWGATVITNLFSAIPYIGTNLV
  EWIWGGFSVDKATLNRFFAFHFILPFTMVALAGVHLTFLHETGSNNPLGLTSDSDKIPFHPYYTIKDFLG
  LLILILLLLLLALLSPDMLGDPDNHMPADPLNTPLHIKPEWYFLFAYAILRSVPNKLGGVLALFLSIVIL
  GLMPFLHTSKHRSMMLRPLSQALFWTLTMDLLTLTWIGSQPVEYPYTIIGQMASILYFSIILAFLPIAGX
  IENY

As you see, a sequence in FASTA format begins with a single-line description, followed by lines of sequence data. The description line is distinguished from the sequence data by a greater-than (">") symbol in the first column. The word following the ">" symbol is the identifier of the sequence, and the rest of the line is the description (both are optional). There should be no space between the ">" and the first letter of the identifier. It is recommended that all lines of text be shorter than 80 characters. The sequence ends if another line starting with a ">" appears; this indicates the start of another sequence.
you can learn more things about these bioinformatical formats here and here.

Thanks for your answer. I am familiar with sequence formats. I was wondering if there was any format for storing data for dichotomous biological keys.

Please edit your question.

authors: Соня Бурбыгина


text:
Do serotonergic (5-HT2A-mediated) psychedelics elicit stimulant effects?
I know that 5-HT2A partial agonism is the key mechanism of action of serotonergic psychedelics but I also know that some research (e.g. the selective (no activity on any other known receptor sites) 5-HT2A inverse agonist/antagonist eplivanserin was being investigated as a sedative) says that central blockade of the 5-HT2A receptors induces sedation which is in opposition to the effect of 5-HT2A partial agonists.
I have a partial answer to my question. I heard from LSD users that they find it regularly causes sleeplessness for the duration of its effects, which is likely due to stimulant/wakefulness-promoting (eurogenic) effects. Albeit just because it is true for one serotonergic psychedelic doesn't necessarily mean it is true for all serotonergic psychedelics. Especially since LSD affects a wide range of serotonin and other receptor subtypes.

You have some great questions that I wish I knew the answers to.  Just a suggestion, you might want to see if your library can get Goodman and Gilman's for you.  I don't know if the answer to this would be in there, but it is definitely the "go-to" reference book for pharmacology.


text:
How do Benzodiazepines induce Rewarding (Euphoric) effects?
Benzodiazepines are a class of drugs that serve as positive allosteric modulators of the GABAA receptor by binding to their own "site" on the aforementioned receptor. By doing this they produce euphoria and a wide range of effects characteristic of Central Nervous System (CNS) depression (e.g. anxiolysis, sedation, amnesia, mental confusion, muscle relaxant effects).
I know that an interaction with the mesolimbic dopamine ("reward") pathway would have to come in somewhere but where? I also know that GABAergic neurons downregulate activity in the mesolimbic dopamine pathway and that this is how opioids and cannabinoids induce euphoria -- they inhibit the release of GABA from presynaptic neurons in the mesolimbic dopamine pathway. I just find that this would be confusing in the case of benzodiazepines since they increase GABA activity, presumably also in the mesolimbic dopamine pathway thus producing dysphoria and not euphoria.
I just would like to know how they manage to induce euphoria in full (what they do to increase activity in the mesolimbic dopamine pathway that thus leads to euphoria)
Please cite journal articles to substantiate your claims.

Thanks for the edit. Could you be a bit more specific about what you need to know? You seem to be giving the answer in the question.

I think it'll be clear now.

Euphoria is linked  to opioid receptors and (more recently) with the endocannabinoid system. The dopamine pathway you talk about is linked to addiction.


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Can the Human body Synthesise Vitamin D from Phytosterols?
I know that the human body can synthesise vitamin D from cholesterol, but can it do so from phytosterols?

Is this article helpful? http://journal.frontiersin.org/Journal/10.3389/fpls.2013.00136/full Can you also give me a link to an article which states that Vitamin D is synthesized from Phytosterols in the first place.


text:
How do you average Ki values?
It's embarrassing for me to ask this but well such is life. NIMH Psychoactive Drug Screening Program (PDSP) Ki Database is mentioned as the source of the average binding affinity (Ki) values given in Goodman and Gilman but whenever I try to, in some way, confirm that these values are averages obtained from PDSP I get values that are way (up to 10,000 fold) off the values given in Goodman and Gilman. (ps. I am a mathematician too so I know how to take an average, $\bar{x} = \frac{\sum_i^n x_i}{n}$ so you don't need to hold my hand through the calculation with something as simple as the conventional definition of averages) Therefore I have reached the conclusion that I must be doing the calculations wrong. Please show me how to do them correctly. Here's a screenshot of exactly what Goodman and Gilman says that's confusing me:

Oh and yes I am using just the cloned human transporter values not just all the stuff that comes up.

check the units.. may be a μM to nM conversion problem.. verify

Nope, all the units are nM.

it would be better if you can save this page as a document or pdf and put it in dropbox. Or if there is an ebook then please provide the url if it is possible.

The latter would be a breach of copyright and the other I don't quite understand how that would be better.

Sharing the URL: if it is open such as in the books in the NCBI site. Better: so that i dont need to zoom in to see.

Since I asked this question I found out what I was doing wrong in searching for Ki (i.e. I thought the Ki ID was the test ligand and hence I was searching for drugs the wrong way) values but also how, I think Goodman and Gilman got its Ki values.
I think what they did was they searched for the hot ligand that gave the most consistent and numerous Ki values and took the average of the consistent Ki values (with an relative tolerance of ~100% between results). Additionally since I knew the data, as is stated in the page displayed above, was taken 30 June 2009 I was able to eliminate some sources that were probably not available on PDSP at the time. Using this I was able to get consistent averaged Ki values in the vast majority of cases (with like, at most a small handful of exceptions).


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What's the Mechanism of Paradoxical Excitatory Effects with Sedating Antihistamines?
I've been reading the British National Formulary 65 (BNF-65) and it mentioned that in some, especially at higher dosages, sedating (first-generation) antihistamines, can produce paradoxical excitatory (or stimulating) effects and so I felt like asking the age-old question, "Why?" because as I hope is obvious by my questions I am fascinated by drug action and I felt there was no better place to ask this question than here on biology stackexchange.

A reference is needed for the paradoxical effects exhibited by certain H1-antagonists. I found only  one which says: We describe three CYP2D6 UMs who reported paradoxical excitation on diphenhydramine. These cases suggest that in CYP2D6 UMs, diphenhydramine may be converted to a compound that causes excitation due to the abnormally high CYP2D6 activity... Although these are only three anecdotal cases of paradoxical excitation from three CYP2D6 UMs, the reports illustrate the need for larger, more formal studies .... Not a strong evidence.


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Why are Taurine and Arginine essential components of the feline diet?
Taurine and arginine play a key role in the feline diet but I am unaware as to where exactly they fit in.

From the Taurine Wikipedia article:

The absence of taurine causes a cat's retina to slowly degenerate, causing eye problems and (eventually) irreversible blindness – a condition known as central retinal degeneration (CRD), as well as hair loss and tooth decay. Decreased plasma taurine concentration has been demonstrated to be associated with feline dilated cardiomyopathy.

Arginine is an Essential Amino Acid for cats (and many other mammals - including Humans while we're infants). That is, they cannot synthesize it on their own and must obtain it entirely from their diet. A 10lb. (5kg) cat will require about .86g of Arginine - which is abundant in all meats and can be met with a few ounces of food.
I could not find anything particularly special about Arginine as opposed to other EAA's for cats.

Arginine is not essential for adult humans. Cats and dogs probably (I don't know for certain but I'm guessing) require arginine because of its crucial role in the urea cycle and their high rate of ammonia production as a result of amino acid catabolism for energy production.

Oh and for me to accept your answer regarding Taurine I am going to need something to back that up I saw that article before you mentioned it but I wanted something more scholarly than wikipedia

Depending on who you ask, there are between 8-10 EAA's. Arginine is required during pediatric development, thus it's my habit to include it. Feel free to follow the links from the wikipedia entry (60, 61) at the bottom. The original studies are from the 1980's and I cannot access them as the website is currently taking too long to respond.

arginine is a conditionally essential nutrient in humans - but essential in cats - I will put some effort into this and place an answer


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Difference In Telomeres Between A Thale Cress Plant And A Methuselah Tree
From what I have read and understood telomeres cap off how many times a cell can divide before it can no longer divide and that is what causes aging.
A thale cress plant apparently has a life cycle of 6 weeks before it dies, while the Methuselah tree has set the record at over 4,800+ years.

What is the difference between these two plants regarding their telomeres?
Is the cell division rate different between both plants instead of a telomeres difference?
If given ideal conditions what could the potential life-span of a Methuselah tree be?

Btw you don't have to answer all these. Just curious and looking for some insight into why the stark difference between both plants' aging.

Telomeres do not "cause" ageing as such - although you are right that they limit the number of times a somatic cell can divide.
Each time a cell divides the chromosomes are replicated in an imperfect way, and as such a small amount of DNA is lost from the end of the chromosome during each round of cell division. Telomeres are just extensions to the chromosomes, so that the DNA that is lost is not important. When a cell runs out of telomeres it ceases to divide.
However it is a big generalization to say that telomere length is therefore correlated with lifespan. For instance a recent study has shown that mice have telomeres 5-10x the length of humans, but live 30x shorter (1).
Inter-species differences in lifespan
Whilst I am no expert on these 2 plants, it is quite an obvious thing to say that organisms age at different rates. Mice, for instance, live 3 years in a protective environment, whereas humans can live 30x that. The difference is down to the life strategies acquired by natural selection: it is more advantageous for a mouse to develop very fast to reproductive maturity and have as many offspring as possible, because there is a very high mortality rate for mice. Conversely for humans, in takes more than a decade for us to reach reproductive maturity! Our "rate" of development/ageing is lower, which is completely related to our reproductive strategies.
I imagine that a very similar story is true for plants - for some it will be advantageous for them to "live fast, die young", whereas for others the best strategy might be to take a long time creating less, but more robust, offspring.
At the molecular level
I have answered a related question previously (Do trees age on a microscopic level?) which might be of interest to you.
In short, the phenotype of ageing is associated with irreparable damage at the molecular level - be it to DNA, organelles, protein aggregations... you name it! Organisms that have a higher metabolic rate, such as mice, accumulate this damage faster. This gives them the benefit of being able to reproduce much earlier, at the cost of reduced overall lifespan.
Plants age slightly differently, but at the genetic level much the same repair pathways are conserved throughout the kingdoms of life, with some alterations of course - for instance plants seem almost completely immune to cancer (2)!
As I argue in the linked to question above, plants have a potentially indefinite replicative potential, as every cell has the capability of regenerating its telomeres, because plants do not have a conserved germ line as animals do - any cutting from a plant has the potential to create an entirely new plant. This varies from plant to plant of course, and plants are still susceptible to damage, they just have modified/adapted repair pathways to cope with their specific lifestyle.
You ask whether it is the telomeres or the "rate" that differs between the plants - the answer is almost certainly a combination of both, amongst the other myriad of factors that influence lifespan!
Refs

Colado, et al, 2013. Telomere dynamics in mice and humans. Seminars in hematology [PubMed]
Doonan & Sablowski, 2010. Walls around tumours - why plants do not develop cancer. Nature reviews cancer [DOI]


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Effects of exercise on the brain
I am well aware of the phenomenon of neurogenesis induced by exercise, as well as the dopamine release that results from exercise. I am really interested in neuropsychology and the effects of exercise on personality. What are some other biological processes that are stimulated by exercise, does it activate our parasympathetic nervous system? Is there any cool research out there for me to read? I am grateful for any input. Any information about exercise and its effects on human biology is appreciated.
UPDATE
While this answer was appreciated, i'm interested in other biological processes... What happens to stress and anxiety? Do our adrenal glands stop secreting as much corticosteroids? What effect does exercise have on circadian rhythms? With exercise, can you circumvent the problem of not getting enough light in the winter? What effect does exercise have on memory? It should probably help, since it would lead to decreased damage to the hippocampus. How does exercise effect sleep, learning, memory, metabolic processes??? I'm searching for the comprehensive list of different primary and secondary effects of exercise from a biological standpoint. I'm really interested in what the short term and long term effects of exercise are on the brain.

There's one thing I can add, I'm pretty sure any dopamine release would be catalysed by a endorphin release seeing how beta endorphin is well known to be released during exercise.

Although current research has little to say about the effects of exercise on personality, there has been recent correlations demonstrated between personality and the "drive" to exercise--specifically, aggression as a personality trait has been linked to higher metabolic rate. See http://phys.org/news206006380.html for more information about this.
The causation in exercise-induced neurogenesis is not well understood. A correlation that has been found (in mice) is the presence of a hormone called beta-endorphin, which is attributed to positive affect (a boost in mood). Exercising mice that demonstrated the presence of beta-endorphin in their hippocampal region did experience exercise-induced neurogenesis, while those that naturally lacked beta-endorphin did not experience neurogenesis.
The basic worth of circulation should not be overlooked, either. Anything that gets your blood pumping more efficiently means that the more distal parts of the body will appreciate an influx of nutrients. A smoker with poor circulation (as a result of lowered oxygen in the blood -- carbon monoxide competes for hemoglobin-binding) will have cold hands and brittle fingernails, and this is just a simple example of this phenomenon. The value of increased circulation to the brain shouldn't be overlooked -- the blood is our main transportation system, and the brain gets nothing that is not delivered via circulation. It's akin to watering a plant -- sure, it may grow it you give it 30 minutes of sunlight and 1/4 cup of water a day, but it will certainly grow to its full potential if it is fed as much as it needs.
Exercise is important, but it's easier to think about the questions you pose if you consider exercise more as a physiological stressor on the body. Muscle tissues are torn and damaged by exercise, but the body recognizes that it must need these resources (because of some present danger in the environment that caused you to run/strain yourself) so you begin to see the typical skeletal muscle hypertrophy. The heart is also made stronger through this strain, which is why regular exercisers have a lower resting heart rate -- it takes their heart less effort to pump the same amount of blood.

Exercise stimulates various hormones which have impact on brain as well as other parts of the body. In psychological perspective, endorphins and serotonin released during exercise, are responsible to feel good feeling or act as antidepressants. Endorphins are produced by pituitary gland in the brain. Serotonin is also produced in brain to some extent during exercise. An increased level of serotonin could lead to nausea and vomiting. The other hormone released significantly is dopamine which is responsible for increasing blood pressure but it also helps in focus, attention and increase memory.

Note that the pituitary gland is not part of the brain. Also, I would refrain to say "release of  does XYZ". Dopamine has many different effects depending on what part of the brain releases it and where.


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Why is the frog genome so much larger than a fish's?
As we have heard in the summaries of the human ENCODE project, 80 per cent of junk DNA appears to have an essential function. Many fish have a genome with only one tenth the size of a usual vertebrate genome. Why can fish have 1/10th of junk DNA and be still fully functional? What has a frog more than a fish has? I'm especially interested if we can see the difference somewhere, complexity of physiology or anatomy, or such.
Jap. puffer fish genome: 390 Megabases, 47,800-49,000 genes (UniProt)
Medaka genome: 690 Megabases, 24,600 genes
Clawed frog: 1,500 Megabases, 23,500 genes

I think this question, like at least a few others, is based on a misunderstanding of ENCODE’s use of the word “function”. Maybe we should have a kind of FAQ for that. (Disclaimer: I agree with their usage of the word. Others, e.g. Larry Moran, disagree – vehemently.)

Genome size is a poor indicator of an organism's complexity (already an ill-defined term). We cannot assume by any means that a larger genome corresponds to a more "complex" organism. There are some plants whose genomes are larger than most mammals, and indeed the largest eukaryotic genome (at least as of 2010) is the plant Paris japonica, weighing in at 1C = 152.23 pg (compared to Homo sapiens at 1C = 3 pg). Anecdotally, in my previous research lab I discussed with a colleague a fungal species whose genome size differed by orders of magnitude between different individuals of that species.
It should never surprise you to see an organism with a larger genome size than what you may consider to be a more complex organism.

Just saw this on Twitter, and wanted to point it out. https://twitter.com/DanGraur/status/372712933525946368

See here for an ENCODE author's reflections on their use of the word "functional". (I don't think anyone is using the word "essential".)
It is clear from this that, for them, one class of functional DNA is intronic DNA: i.e. introns are defined by ENCODE as functional DNA. It is well known that puffer fish have reduced genomes and that this is largely due to the presence of much smaller introns, although the number and positioning of these introns is broadly similar to what is seen in other vertebrates. One classic example of this is the huntingtin gene which is 7.5 times shorter in pufferfish than in humans even though both genes have 67 introns. In fact the average fish genome size is 5-6 times bigger than that for pufferfish (zebrafish is around this average value).
Although ENCODE are defining intronic DNA as functional I don't think that they are claiming a specific function for each and every intron, let alone each base in those introns. So there is still  a lot of scope for the observed differences in genome size.

I think the last paragraph nails it (and, incidentally, the controversy about ENCODE’s 80% figure) – although intronic DNA is just a small part, much more is in repeat elements.

That's a good read!


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How is it possible to even hope for an ebola epidemic of this current size to remain contained to a relatively small part of Africa?
As of 2014-09-14 at least 5347 cases of ebola have been identitied. Some estimates are much higher. While experts are sounding the alarm to try to get sufficient resources to contain the outbreak, some people are also speaking very hopefully about containment to roughly the current affected area. This article puts the risk of the outbreak reaching the United States as low as 3%. I'm not an expert in the field, but it seems like there are almost countless ways in which an increased number of cases increases the risk of further exponential growth. It's encouraging to hear that in countries with better healthcare, death rates would likely be much lower, but at this point, isn't it inevitable that the outbreak will run its course as a global pandemic?
For example, which of these possibilities is just my imagination, or likely so improbable that we don't need to worry about it?

Scared carriers not yet showing symptoms sneak or force their way across boarders to unaffected regions.
Objects, food, or water touched by the infected go unnoticed until they end up leaving the containment zone.
If it can jump from bats or monkeys, thousands of infected humans increase points of contact to create vectors into other species, perhaps one that will travel unnoticed far beyond the containment zone.
After months of the same security precautions day in and day out, airport checkpoints, and other points of entry become lazy, and let infected through.

With numbers as high as they are, and possibly higher than we even know, is this really containable at all?

The thing to know about Ebola is that it really is not that contagious - you need to be in direct contact with someone else's blood. While this may occur in undeveloped countries, it is very unlikely to occur often in the US. Any cases in the US would be immediately dealt with, and would any deaths. This is true for most of Europe etc., as well.
Countries strongly affected (like Sierra Leone) have also not been using the most effective epidemiological policies, and perhaps even causing harm by, e.g., enforcing quarantines.

The key is "you are not getting contagious unless you show symptoms" so it is unlikely in the west that we will get more then small scale outbreaks.

This is too long for a comment, so my thoughts about this here. The CDC Director said a few days ago after a visit in Africa "The window of opportunity is closing".

This can happen. However, you are not getting contagious unless you show symptoms. This is different in other diseases like chicken pox or measles where you spread the virus before showing symptoms. So there has to be a lot of awareness. Also doctors need to be very careful with patients showing these symptoms. This is most likely one of the main reasons for the wide spreading of the disease.
Same problem as in 1. Theoretically this is easy to prevent, but in a situation of chaos this can cause problems. But since infected people which show symptoms will not handle large amounts of food, this is most likely less of a problem.
Every crossing of a species-barrier is a rare event. Double-crossings are even less likely. So I don't think this is a problem. Besides this, we already have to independent Ebola outbreaks which has never happened before. One is the one in West-Africa, the other one is happening in the Democratic Republic of Congo. Both are independent cross-overs.
This can cause problems. The advantage of the first world is that we have functional health care systems. They allow better care for the persons and also better isolation of contact persons. I think it is unlikely that it would spread widely. The perspective will be different, if the virus makes the jump into the densely populated regions in South-East Asia. There a lot of people live closely together, this can cause real problems. Fortunately for us the virus is not highly contagious. To infect yourself you need unprotected contact to the body fluids (blood, stool, feces, sweat etc.) of infected persons.

"Not highly contagious" is encouraging. It seems easy enough to avoid infected person's blood, feces, vomit, etc. But sweat... We sweat all the time even if we aren't particularly hot. An infected person must sweat a lot more. Doesn't that get the virus all over everything?

Yes, this is one of the problems. This is also the reason why peope of the isolation wards are dress up like they do.

@MarkBailey, yet but UV light kills it.   And infected people do not feel well, so in the west are unlikely to travel much.

I'm not an expert in the field, but it seems like there are almost
  countless ways in which an increased number of cases increases the
  risk of further exponential growth. It's encouraging to hear that in
  countries with better healthcare, death rates would likely be much
  lower, but at this point, isn't it inevitable that the outbreak will
  run its course as a global pandemic?

I don't think it is inevitable. The current strain has a high virulency, high mortality, but low transmissibility. It does not infect until the patient shows symptoms, but by most of that time she/he will be unable to move and spread the infection because of the 39°C degree fever. Only the people nursing the patient, e.g. family members, workers in the healthcare system, are in danger. So it spreads slowly compared to other diseases and that's why it is easy to quarantine and prevent. If it does not change attitude due to a mutation or anything else, I think we can avoid a more serious pandemic, at least I hope so.
There is an already existing model for an older strain available here: Understanding the dynamics of Ebola epidemics.

Scared carriers not yet showing symptoms sneak or force their way
  across boarders to unaffected regions.

I have the impression by listening and reading news, that most of the people know nothing about ebola in Africa, or they don't really care, because they cannot read, or they have bigger problems e.g. starving. For example Sierra Leone is one of the poorest countries in the world. They cannot move so easily, because travel requires money. So I think this is possible, but unlikely. If it happens, the infected person cannot spread the disease fast, because she/he will be unable to move after showing the symptoms. So she/he can be quarantined.

Objects, food, or water touched by the infected go unnoticed until
  they end up leaving the containment zone.

I think in the current case this is unlikely either. But if a food contains virions, it does not necessary cause disease, e.g. microwave oven, or long shipment - usual by fruits like banana - can inactivate it.

If it can jump from bats or monkeys, thousands of infected humans
  increase points of contact to create vectors into other species,
  perhaps one that will travel unnoticed far beyond the containment
  zone.

Well, it needed 8 changes to fully adapt to guinea pigs. (It was possible to infect these animals, but the outcome was not lethal.) The virions contain 19kb of RNA, and the mutation rate is 2.0 x 10^-3 substitutions per site per year. Now I am not an expert of genetics (I always hated it), but as far as I understand it is possible to rougly estimate the risk based on this data. I guess it would take decades to adapt to another species, so it is not a fast process.

2013 - Animal models for Ebola and Marburg virus infections

Comparative sequence analysis of the complete genomes of the GP-adapted
  EBOV and wild-type virus showed 8 nucleotide differences, which led to
  5 amino acid substitutions; single amino acid mutations in NP and L
  and 3 mutations in VP24 (Volchkov et al., 2000). Using a reverse
  genetics approach, it was shown that VP24 had a critical role in the
  pathogenesis and the amino acid changes in VP24 were essential to
  achieve EBOV virulence in guinea pigs.

2013 - Ebola virus infection inversely correlates with the overall expression levels of promyelocytic leukaemia (PML) protein in cultured cells

Ebola virus belongs to the family of negative strand RNA viruses
  (Mononegavirales) and together with the Marburg virus are the two
  known species of the Filoviridae family 1. Electron microscopy of
  Ebola virions produced in cell culture have shown them to be
  pleomorphic, appearing as either 6-shaped, circular or as long
  filamentous (and sometimes branched) forms with a length up to 14,000
  nm and a uniform diameter of 80 nm 2. The 19 kb single-stranded RNA
  genome encodes seven viral proteins: the membrane associated (matrix)
  proteins VP24 and VP40, the viral glycoproteins, GP (that forms the 10
  nm long peplomers) and sGP (non-structural secreted form), the
  characteristic helical ribonucleocapsid that consists of the
  nucleoprotein (NP), VP30, VP35 and the L-protein that forms a
  RNA-dependent RNA polymerase 1.

wikipedia - Ebola virus

Sequencing of 99 different Ebola isolates from patients in the 2014
  West African outbreak of Ebola showed the virus to be rapidly
  mutating,[15] with a mutation rate of 2.0 x 10-3 substitutions per
  site per year making it as fast changing as seasonal influenza.[16]
  This is likely to represent rapid adaptation to human hosts as the
  virus is repeatedly passed from human to human (as opposed to usually
  being passed between fruit bats and only occasionally crossing over
  into humans), and may pose challenges for the development of a vaccine
  to the virus.[17][18]

After months of the same security precautions day in and day out,
  airport checkpoints, and other points of entry become lazy, and let
  infected through.

I don't think security works this way. Btw currently we have the technique to filter out people showing symptoms, for instance with IR detectors looking for elevated body temperature. We have e.g. ELISA for checking IgM or the presence of the virus itself in blood tests. So if these measures are needed, I think we will apply them. Currently they are not needed, according to CDC there were only 5 cases outside Africa.