text:
Inbreeding depression and dominance
From this article,  second paragraph of the second page

A classic theoretical result is that the mean of a character controlled by a single locus i with two alleles Ai1 and Ai2 is only affected by the value of f if there is some degree of dominance.

where f is the Wright's inbreeding coefficient.
The authors then add:

Assume that the trait is scaled such that the values for the genotypes Ai1Ai1, Ai1Ai2, and Ai2Ai2 are -ai, di, and ai respectively. The quantities ai and di measure the effect of the locus on the character and the degree of dominance of the locus, respectively. With two alleles, there is a linear decline in the mean of a trait
  with increasing f either with overdominance (di > ai) or if the allele associated with an increased value of the trait is dominant or partially dominant (ai ≥ di > 0). With additive joint effects of different loci on the trait, this conclusion can be extended to a polygenic character; inbreeding decline occurs if the average value of di over all i is positive.

I don't understand why "[..] there is a linear decline in the mean of a trait
with increasing f either with overdominance (di > ai) or if the allele associated with an increased value of the trait is dominant or partially dominant (ai ≥ di > 0)"
Can you please explain why the mean of a character controlled by a single locus is only affected by the value of "f" if there is some degree of dominance.

Recap of the question:
Looking at a single locus trait ($A$) controlled by two alleles, $A_1$ and $A_2$, the phenotypic mean is only affected by inbreeding depression, $f$ (Wright's inbreeding coefficient), if there is some degree of dominance, $d$. Why?
Answer:
If we take inbreeding as a higher than expected frequency of homozygotes, such that if the frequencies of alleles $A_1$ and $A_2$ are $p = q = 0.5$ the expected frequencies of the genotypes in an outbred population, $P_{outbred}$, would be $p^2 = 0.25$, $2pq = 0.50$, and $q^2 = 0.25$.
Each genotype has the following phenotypic result on a trait $A_1A_1 = 5$, $A_1A_2 = 7.5$, $A_2A_2 = 10$... this is an additive trait with allele $A_1$ having an additive effect of 2.5, and $A_2$ an additive effect of 5.
We can then compare an inbred population of 100 individuals, $P_{inbred}$ where the frequency of $A_1A_1 = 0.5$, $A_1A_2 = 0$, $A2_A2 = 0.5$, to $P_{outbred}$ , where I use $\bar{X}$ to symbolise trait means.
$\bar{X}_{inbred} = \frac{(50 \cdot 5) + (0 \cdot 7.5) + (50 \cdot 10)}{100} = 7.5$
$\bar{X}_{outbred} = \frac{(25 \cdot 5) + (50 \cdot 7.5) + (25 \cdot 10)}{100} = 7.5$
So when the trait is additive the population means are equal. It is onlt when we add dominance to the situation that the population means will differ as a result of inbreeding. Continuing from the above example, the populations are the same size and structure, but $A_2$ is now completely dominant to $A_1$ such that $A_1A_2$ individuals now have a trait value of 10. Now
$\bar{X}_{inbred} = \frac{(50 \cdot 5) + (0 \cdot 10) + (50 \cdot 10)}{100} = 7.5$
$\bar{X}_{outbred} = \frac{(25 \cdot 5) + (50 \cdot 10) + (25 \cdot 10)}{100} = 8.75$
Thus inbreeding has affected the population mean in a trait which has dominance, it is basically because the heterozygotes are less common in an inbreeding population and this is where dominance effects are seen.

"there is a linear decline in the mean of a trait with increasing f... with overdominance (di > ai)"

This is because in the case of overdominance, the outbred population mean becomes even more elevated - if we say now the $A_1A2$ trait is a phenotype of 15 the means become
$\bar{X}_{inbred} = \frac{(50 \cdot 5) + (0 \cdot 15) + (50 \cdot 10)}{100} = 7.5$
$\bar{X}_{outbred} = \frac{(25 \cdot 5) + (50 \cdot 15) + (25 \cdot 10)}{100} = 11.25$

" there is a linear decline in the mean of a trait with increasing f... if the allele associated with an increased value of the trait is dominant or partially dominant (ai ≥ di > 0)"

The mean will increase if the dominant allele produces a smaller phenotype. Here we say $A_1$ is now completely dominant,
$\bar{X}_{inbred} = \frac{(50 \cdot 5) + (0 \cdot 5) + (50 \cdot 10)}{100} = 7.5$
$\bar{X}_{outbred} = \frac{(25 \cdot 5) + (50 \cdot 5) + (25 \cdot 10)}{100} = 6.25$
I hope that answers the question, I tried to answer last night but was too tired to think - this is just what I came up with on the walk to work today so I haven't had the time to check it/overthink it

Yes, that answers my question. It is actually a very good "for dummies" explanation of a fairly complicated text. You answered so many of my questions this week. Thanks a lot!

haha - there's been a bit of activity to try and get the unanswered Q's reduced, there was a comment in the chat room that probably the only person to answer some of your unanswered Q's was me so I set myself the challenge of answering 5 this week... two to go! @remi.b


text:
Are all Y-chromosomes the same?
Since the Y-chromosome can only pass from male to male child, it would seem to pass intact. Thus, a boy's Y-chromosomes would, I guess, be the same as his father's. Going backwards, would not all men have identical Y-chromosomes for this reason, being somewhat like mitochondrial DNA?

Because the Y stops recombining and has a small population size it is expected that variation will be rapidly depleted.  Mutations still occur on the Y which can maintain some within population variance. http://www.ncbi.nlm.nih.gov/pubmed/26230387

There is a difference between an evolutionary process and a genetic process so to speak: you don't need recombination for evolution. A lot of organisms use cloning to generate "offspring", but these evolve as well because of mutation.

Actually, no. There are also recombination prone regions of the Y chromosome that recombine and exchange material with X chromosomes, and these are called pseudoautosomal regions (PARs).
Y chromosomes can be used similarly to mitochondrial DNA to build up profiles of ancestry, but the sequences used for this purpose lie outside PARs, in the non-recombining region.
What about seqeuences outside PARs, do they show genetic variation?
As pointed out in the comments, PARs comprise only 5% of the Y chromosome, but even in the non-recombining regions of the Y chromosome studies in well-characterised populations have found that the mutation rate can approximate autosomal mutation rates in some regions of the chromosome, and exceed them in others.
What processes, other than recombination, drive mutations?
There are loads of different mechanisms by which mutations in general can be generated, including exposure to UV, free radicals, tobacco smoke, aristolochic acid, and perhaps most importantly spontaenous deamination of methylcytosines, which is an age related mutational process, proofreading errors inherent to DNA polymerases. Also, it is well known that in sperm, with age the mutation rate goes up throughout the genome. While UV is unlikely to be a prominent mutagen as was pointed out to me in the comments insofar sperm are concerned, factors like smoking still play a role.
An illuminating read about mutational processes and the mutational footprints they leave in genomes, as understood from studying cancer genomes, is here.

Ok, but those regions are only 5% of the chromosome. Is the other 95% the same in all men?

Nope - those regions too are subjected to mutations at various rates, that in some well characterised populations approximate the autosomal mutation rate in some regions of the Y chromosome, with other regions showing elevated mutation rates.
http://www.nature.com/ng/journal/v47/n5/full/ng.3171.html

Without recombination, how is the chromosome mutating? I know that it might get struck by a cosmic ray or something, but barring that, how?

There are loads of different mechanisms by which mutations can be generated, including exposure to UV, free radicals, tobacco smoke, aristolochic acid, and perhaps most importantly spontaenous deamination of methylcytosines, which is an age related mutational process, proofreading errors inherent to DNA polymerases.
Also, it is well known that in sperm, with age the mutation rate goes up throughout the genome. http://www.nature.com/news/fathers-bequeath-more-mutations-as-they-age-1.11247

One of the places where mutational processes and signatures have been best studied is in cancers; and this paper should make for illuminating reading. http://www.nature.com/nature/journal/v500/n7463/full/nature12477.html

I am not sure if you can have UV exposure on your list, as I do not think it is likely that UV has the energy to penetrated deep enough into the tissue to cause damage to germline cells, which is the only way to pass on mutations. More energetic EM waves such as X-rays obviously could do the damage, but there you start to have to think about how much damage can be done before the sperm is ineffective. I am also not sure if there are mutagenic effects to germline cells from tobacco smoke. I could see where you might get decreased fertility due to vascular changes. I agree with the others.

@AnkurChakravarthy please can you edit all of your comments into the body of your answer: they make it a much stronger answer, and it means they will be preserved long after the comments are deleted (comments are ephemeral, questions and answers are to keep)

@ImprisonedRhesus That's what mutation is. Crossovers and similar "operations" are not mutation - only DNA damage is. Apart from what Ankur already mentioned, there's a few more interesting ways - for example, errors when repairing damaged DNA. By far most of those happen in your somatic cells, of course, so they are not long-living, and they do not propagate to your offspring, but there's still plenty that affect your germ cells (not to mention possibly affecting the development of an embryo, where there's a chance to affect the whole organism rather than just a cell or two).

@AMR It's not about having too little energy, really - visible light penetrates far deeper than UV. But other than that, I think you're right - the deepest penetrating UVA only penetrates about 4mm. It might be possible a small amount penetrates deep enough to affect germ cells, but probably not significant enough to matter.

@AMR I don't think you read my comment right - visible light (lower energy than UV) penetrates deeper. It's not a matter of bigger energy penetrating deeper - rather, it's about the energy levels available for absorption (after all, how else would different materials be transparent to different spectra of light?). If you want to know how X-ray imaging actually works, it's a very interesting subject (bones are indeed absorbing a lot of X-rays, but we get a lot more information from scattering, which also happens in soft tissue).

@Luaan you are correct about absorption, I was mixing my arguments. This figure illustrates your point well. http://ec.europa.eu/health/scientific_committees/opinions_layman/artificial-light/en/figtableboxes/8.htm

AMR - I agree UV is likely to be a weak contributor to germline mutations. Smoking on the other hand has been shown to be a germline mutagen (see http://humupd.oxfordjournals.org/content/6/2/122.full.pdf)
EnergyNumbers I will make that edit.

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sort: votes


text:
mutations induced by transposons
Question:
In contrast to chemically-induced mutations, mutations induced by transposons are more likely to ...

be lethal
de dominant
be stable
revert to wild types
be a gain of function

The answer is 4; but I have no understanding of why this is the correct answer, or, why the others answers are not correct.  Could someone help to explain why this is the case?

Transposons are mobile genetic elements, or jumping genes. If a Tn can jump into your gene then it can also often jump out again later, so sometimes the mutation reverts. This means the mutation is unstable, so 3. is incorrect. As an RFLP the Tn is dominant in a diploid, but usually a Tn mutation causes a recessive loss-of-function phenotype, so 2. and 5. are incorrect. In a diploid a recessive cannot be lethal on its own, because then it would be dominant, so 1. is incorrect.

@mdperry you can make that an answer. However, transposon can affect the X chromosome of the male and can show dominant effects. But since that is only a specific case we can dispose it.

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text:
Aerobe or facultative anaerobe organism that metabolizes acetate?
I'm assuming bacteria, but will take any suggestions.  Organism must survive primarily on the acetate (plus trace elements), but I can give/take electrons, if necessary.  Not interested in strict anaerobes.  I've tried Shewanella oneidensis, but have not succeeded in getting it to eat any acetate (just lactate).  Feel free to give journal refs.  Self-promotion won't be frowned upon if it's helpful.  :-)  Opportunity for joint pub, if successful.

You could try Paracoccus denitrificans.
Here is a study where acetate is used as the growth-limiting substrate: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.320.1692&rep=rep1&type=pdf
Here's the details of its version of acetate kinase: http://www.uniprot.org/uniprot/A1B9S8
I'd be happy to collaborate with you further on this.

Thanks for the info.  In this paper, the acetate is only 0.34% (v/v).  Do you know if P. denitrificans can handle higher concentration, say 1% to 3%?  (Many organisms are killed by acetate, hence pickling to preserve food.)  Or is 0.3% its limit?

This study: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC182557/?page=1 has P. denitrificans at 1% v/v sodium acetate. I don't know how much higher it can go though.


text:
Does Lucid Dreaming decrease the regenerative effect of sleep?
After watching this SciShow video on sleep, I wonder about lucid dreaming.
Specifically: Does lucid dreaming and associated directed agency within Lucid Dreaming decrease the regenerative effect of sleep?
That is, if I gained the skill of lucid dreaming - would I be negatively tampering with the brain's autonomous healing processes for the period that I had conscious control or even simply objective awareness during sleep?

I am not sure about biology, but from what I feel of lucid dreaming, I, contrary to decreasing the regenerative effect on sleep, can increase it, since I am able to choose what dream states are the most refreshing. I have also noticed that sometimes it is enough to reach a particular states and dream and see particular things to get the tiredness load off in just a few seconds (of experiencing a particular dream). That never frees you from the requirement of the full-scale normal sleeping, but comes handy in some situations

It's possible that they do, depending on the intensity of the dream and the amount of brain activity.
For example, if the dreamer is thinking too much or is having a dream that's way too intense, the brain activity goes up and they're not as rested.  However, lucid dreaming can be good for sleep if the dreamer creates a more relaxed dream.  This can possibly be better for the sleeper, especially if they're someone who experiences nightmares every night.
Basically, it just depends on what you're dreaming about.  The calmer and more relaxing the dream is, the better.
Source:
-www.world-of-lucid-dreaming.com

Welcome to Biology. It would be great if you could add some references to your answer.

A scholarly source would be preferred to fan site / infomercial.

That's true.  Should I just take my answer down, then?

You could edit it?

If you can't edit it, you could make a comment out of the answer. Those kind of comments can be very helpful.

Yes, when you are dreaming, brain activity increases ( called the REM phase because of the effect of the increased neural activity: rapid eye movements ).
You can tell this by looking at the EEG, from witch we can state that our brain is more active and therefore is consuming more energy, making the regenerative effect of the sleeping less efficient.
https://en.wikipedia.org/wiki/Rapid_eye_movement_sleep#Electrical_activity_in_brain


text:
What is the secondary structure distribution per AA in the Human proteome?
If one would classify each amino acid to either be in a Coil, Beta strand or Alpha helix what would be the distribution of these classes in the human proteome?
Is it 33%-33%-33% or is it biased? If it is biased why?
I thought it should be around equal, but I run the whole proteome through PSIPRED, and I found the distribution to be 60% Coil, 30% Helix, 10% Sheet. Why is it so?

I'm not sure what you're asking here. You seem to have answered your own question about the distribution (interesting, by the way!). So, by your own data, it is obviously biased. I don't know much about proteins, I'm a genomics person, but why would you assume no bias? Also, are you looking percent of total amino acids? Percent of total protein in each conformation? A bit more detail would be helpful.

A percent of amino acids in each secondary structure. I am just not really believing by own results, as far as i remember from the university these should be near equal (or like little bias). there are aprox 20k proteins in the human proteome, if we say each consist of 500 AA, we roughly get 10 million amino acids, which is in contrast with my results, as i get 6 million AAs in coils, 3 million in helix, and 1 million in sheets.

While I strongly object to the tone of the answer you've received so far, I see no reason whatsoever to assume an equal distribution. The properties of the different structures are not the same, so it doesn't make sense to expect such a distribution. Some explanation of why you would make such an assumption might be a helpful addition to your question.

The only answer I could give is very vague, unfortunately.  The distributions are not equal because these three SSE types play quite different roles in 3D structures. Sheets usually form in the core of a folded structure, and are short. Helices tend to pack around the outside, and can be longer. 'Coil' is everything else, and covers structure like long loops.

A major problem with my answer is the distribution of folds. If genomes were packed full of helical bundles, then the proportion of helix would go up. Presumably an organism with a lot of excreted extracellular proteins (that tend to have little secondary structure) would have a higher proportion of coil, and so on.

The question asks why the distribution of coil, alpha-helix and beta-strand is 60:30:10 rather than 33:33:33. The answer is:

“Why not”

This is because there is no reason whatever to expect that three types of structure (or in the case of coils, lack of structure*) should be present in equal amounts in proteins. It is like expecting that the percentage intron, exon and ‘junk’ DNA should be equal, or that the percentage of fuel reserves stored as glycogen and fat should be the same. Yes, they belong to the same category, but they are sufficiently different in each case for one not to be surprised if they are not required in equal amounts.
To understand this one needs to look a little more carefully at the occurrence of alpha-helix or beta-strand conformation in the three-dimensional structure of proteins. Three points may be emphasized:

Amino acids have particular conformations because they are part of an extended helix or sheet of strands the entirety of which leads to its structural stability — you don’t have a random mixture.
In many cases the helices or sheets are occur in particular combinations to give a family of proteins of similar overall structure. Again, the idea of random mixtures doesn’t enter into the equation.
These overall structures are suited to particular functions, so the abundance of proteins from a particular structural family will be determined by the requirement for antibodies or ion transporters or signal transducing proteins etc., not by some shake of the dice.

Images illustrating two such families are shown below:

(a) shows an ion transport proteins, predominantly alpha-helices, whereas (b) is an immunoglobulin domain with a distinctive pattern of beta strands (as well as some helix). For further examples and information I suggest the EMBL on-line course on protein classification and Berg et al. online, for example Section 7.3.
*Footnote 1: Situations where equal occurences might be expected
It is worth while contrasting the situation with protein secondary structure to some where the prior expectation might well be for equal usage, and the deviation from this could be regarded as bias and an explanation worth asking for:

The different proportion of the 20 amino acids in proteins (although a chemist would not expect equal proportions)
The different usage of synonymous codons of the genetic code in various species and mRNAs
The different usage of the similar molecules with a high phosphoryl group transfer potential: ATP, GTP, UTP and CTP (often loosely termed ‘high-energy’)

*Footnote 2: A coil is not a secondary structure
As is stated in the Wikepedia entry for Protein Secondary Structure:

The random coil is not a true secondary structure, but is the class of conformations that indicate an absence of regular secondary structure.

It might be mentioned in regard to protein structure that there are smaller three-dimensional motifs that the analysis quoted does not consider. These do not occur in equal proportions either, to nobody's great surprise.

Votes on a question have nothing to do with "sharing the mistaken scientific logic of the question". All due respect, get off your high horse. I upvoted it because I felt the underlying questions (why is such a distribution observed? Why are coils more common?) to be both interesting and worth investigating. Sadly, your answer doesn't address anything in the question apart from the obviously faulty premise.

This is not an answer i am sorry. This is a rhetorical something. I remember something from the university that the percentages of secondary structures are kind of equal. This must be a long known fact (either true of wrong) and all i want is a confirmation.

David, I see from your profile that you've done some structural work. Why don't you improve this answer and actually add something about the relative stability, functional plasticity or any other relevant properties that are different in the different protein conformations and how these can be used to explain the observed ratio?

@terdon — I'll stay where I am, I'm quite comfortable. I certainly answered the question. The reason that they differ from random — that was the question — is because there is no reason they should be random. If the question had been why is there more helix than sheet in proteins I would have voted to close as the answer is a matter of opinion. All you get is the sort of circular argument about something having more general utility. The poster needs to get away from his computer and read about proteins.

@GáborErdős — Your memory from the university is either faulty or you were told untruths. It is not a fact — long known or otherwise. If you do not believe me I suggest you search the internet (or read some books) to find evidence for this and cite it in your question.

@terdon — I've taken out the sentence that appeared to offend. And by the way my work on protein motifs is primarily computational — my colleague is the protein chemist.

@GáborErdős — I have now added some information to my answer to help you understand why your premise was incorrect. I have also restructured my answer and provided reading suggestions. If you are using bioinformatics tools you still have to think about the structure and molecular biology of the data sets you are working on.


text:
Any difference between inverted microscope objective vs normal microscope objective?
I'm planning to build an inverted microscope and I am not sure if I can use a plane achromatic objective of a normal microscope for the inverted microscope as well. Are there any specific needs for the objective of an inverted microscope?

Apart from the way it works and certain structural differences (reference), the decision of which kind of lens you need to use is left to your own personal choice based on your needs. You can find a list of the different lenses being offered by Olympus in this link.


text:
Could a single cell be brought to life?
If a scientist is observing a single cell under a microscope, and then realizes that the cell has died, is it possible to bring that dead cell back to life?
For my inquiry, let's assume that the death of the cell has occurred without disease or external circumstances.
Has such process ever taken place in a lab before? Thx.

this is very speculative and vague - I tried making some changes to improve it....but still vague.

@Vance L Albaugh, thanks for your help, the question is simply about whether a dead cell could be brought back to life or not. Not sure what is vague about this. Please explain the vague point(s) so that I could attempt to clarify. Thx.

How is cell death defined?

@Remi.b, Excellent question. I am not a Biologist by any measure, so I really not sure of the accurate scientific term. However, I would assume that one aspect of cell death would include recognizing that the cell has stopped performing the chemical reactions that a living cell normally performs. However, I am trying to understand, so I may be wrong.

There are species where cells and even whole organisms can go into a state called cryptobiosis where their metabolism is suspended but can be revived later. This usually happens when the conditions become too bad for survival (dry/cold etc.) and is reversed once the conditions improve again (rehydration warming up). One prominent and fascinating example are tardigrades.
Also, it is possible to freeze cells in liquid nitrogen where all metabolic processes are extremely slow. With modern freezing/thawing processes cell survival rates >90% are possible. However, before you ask this will not work on whole tissues let alone people!
Cryptobiosis only works for specialized species and only under certain conditions. Normally, once a cell starts to die, it either does so because it is too damaged to keep living, a process called necrosis or because apoptosis (programmed cell death) was triggered upon which its DNA is fragmented and the proteins are degraded by proteases. Neither process is reversible once started.
Note: I find your restriction "the death of the cell has occurred without disease or external circumstances" a bit puzzling and too vague. Unless something happens to them cells don't just die. Therefore I explicitly ignored this restriction until you formulate it more specifically so that it makes sense.

Thx. for the detailed answer. I assumed that sudden cell death is frequent and normal, yet In this question, I got about 3 people questioning this point which hints to me that sudden death is 'not normal'! I need to do some reading to understand the 'basics of cell death reasons'!

@NoChance If you feel that my answer was correct, please accept it (click on the hollow check mark you see below the voting buttons). Thanks :)

I expected more answers to come for such an interesting question, but you were the only one! Thx.

@NoChance Thx :)


text:
How would one identify cellular transcription factors associated with a viral protein in a treated cell line?
I've been working as the computer guy for a microbiology lab for the past few months. I've always been interested in bench work, but my wet lab experience is rather limited and thus so is my understanding of wet lab techniques.
The PI has expressed his support and given me the opportunity to conduct my own project from start to finish (generation of wet lab data and computational analysis) and write a paper in preparation for my Ph.D school applications.
I realize that coming up with an actual question is a long and thought out process so I want to do my homework before approaching him with a question. I've read quite a bit of literature and have come up with a question i'd like to answer, the computational stuff I can handle and explain in detail, but I'm having a hard time with the wet lab techniques I could use to generate some of the data i'm interested in.
Effectively I am looking to obtain a list of potential cellular transcription factors that are physically associated (bound) with/by a specific viral protein. Is there a lab technique that would allow me to generate such a list?
Links to papers, wikis, your own theories or anything will be greatly appreciated. Also any advice, or "this isn't possible" is all appreciated, as long as you can give me a bit of "this is why".
Thank you! (PS I'm not sure if this type of post is allowed here).
EDIT: It is important to note that I am looking for new binding partners.

Co-immunoprecipitation followed by a western blot comes to mind; you pull out a known TF from lysate with antibodies and then try to detect what you suspect is complexed with it in a western blot with another antibody for the viral protein, or vice versa.

@Kendall this can only be done for TF's that are known or that we believe to be associated with the viral protein correct? What if there is no research on TF's that bind with this viral protein, so I have to actually identify new binding partners (I know this is non-trival and probably an entire paper on its own).

Basically you need to have antibodies to what you are studying, and when you do the actual pull down the hope is your TF is complexed in some way with your viral protein, so that during the western blot if you get detection with the second antibody, you can logically conclude that there is a physical interaction between the two. Co-IP cant discriminate direct/indirect association, however, so if you need to know the direct binding partners, a more complex technique is necessary

If you need to identify new binding partners for some reason, you probably need to do something like tandem affinity purification (basically somehow purify the unknown binding partners) followed by separation and biophysical methods like mass spec.

That second answer is what I was looking for, the viral protein hasn't been studied in the context of binding to host cell chromatin so i'm interested in determining at least one of it's binding factors. Some computational analysis done on another paper my lab has written leads me to believe that the viral protein recruits some regulatory transcription factors in order to bind to chromatin, but there isn't much or anything known about who these TF's are.


text:
What is this blue-green bioluminescent jellyfish I saw at Aquarium of the Pacific?
I took this picture of an animal in the bioluminescent section of Aquarium of the Pacific in Long Beach, California, but I neglected to write down what it was.  I've searched the Aquarium's web site, but it doesn't appear to have information about the individual species on exhibit.  (Or else I just can't find it.)  I've also looked at Wikipedia and Google Images, but can't seem to find a creature that looks like this one.
I suspected it could be a jellyfish, and the answer below confirms that.  But I'd like to know what species of jellyfish it is.  (Either common name or scientific name.)

After sifting through even more images on Google Images, I think I have finally identified this as the flower hat jelly, Olindias formosa.  (Wikipedia, Monterey Bay Aquarium)
The coloration looks different on those sites, but I think it's just a matter of lighting.

I think they probably have it under UV blacklight at the Aquarium of the Pacific. So it's probably not bioluminescence, but UV fluorescence,

Thanks for that tip!  I did some further research, and this article seems to confirm your hypothesis.

That is a Jellyfish! :D
Someone else took a picture of that same Jellyfish:
http://www.yelp.com/biz_photos/aquarium-of-the-pacific-long-beach?select=36BuiiqeN7OIFbowSDkPcw
Here is a picture from an article about the exhibit's jelly fish:

Source: New Jellies Exhibit at Aquarium of the Pacific Explores the Mysterious Lives of These Gelatinous Sea Creatures

Thanks!  I'd suspected it might be a jellyfish, but I wasn't sure.  I'd still like to know exactly what kind of jellyfish it is.  Unfortunately, the linked article doesn't have captions on its pictures.


text:
What equipment would one use to modify a virus?
Would anyone be so kind as to give me a few examples of the equipment involved when modifying a virus? Otherwise my novel may end up reading
Eva entered the lab and modified a virus.
Not much back story there!

Even though you actually intend to get the facts right for your story, it is better to ask it as a biology question. It would be great if you can edit the question to sound so. Otherwise this question is tending to be off-topic.

To help you frame a better question I can give you this hint- To modify a virus, you have to modify its genome (DNA or RNA in some cases) :)

(I voted to close because it appears to be homework & is too broad)

I actually am an expert at this, and I have always wanted someone to use forward genetics in a well researched piece of fiction for what it's worth.  Feel free to try and ask more targeted questions, and I'd be happy to answer.  I would also like to point out that considerable amounts of time and failure are to be expected.  Even on a proven recombinant system I would put 1 month minimum to recover, purify, titer, and sequence a new virus.

I'm no expert at this and I would welcome any changes to this post. First you need to decide, what your target organism which you want to infect is (e.g. mammalian cells, bacterial cells) and based on that you choose your viral vector as listed in this article. Generally for mammalian cell stable transfection (usually you want the genetic materials you introduced to persist between cell divisions hence stable transfection) and transformation (just a general statement about changing cells as you have introduced, usually foreign genetic material but transformation is not necessarily the same as making something immortalised, which means the cells won't stop dividing i.e. becoming cell lines or in lay term cancerous) scientists tend to use lentiviruses, which are retroviruses, similar to HIV and they can even infect non dividing cells (so this should allow your imagination to run wild!). Once you have decided what the best viral vehicle for targeting your cells of interest is then you essentially transfect the plasmid DNA (packaging vector), which produces the virus protein package, into cells, whose job becomes to produce the virus as those cells have the required cellular machinery for this purpose. These cells are often 293T packaging cells. Along with the plasmid (circular) DNA, which produces the virus package, you co-transfect the packaging (e.g. 293T) cells with another plasmid, called lenti-vector, which does whatever you want it do, such as express a particular protein or microRNA or whatever but the idea is that stuff produces by the lenti-vector should not be toxic to the target cell (i.e. the cells you intend to target), unless thats what you want it to do.
Now as you can see, you can play around with two things here, first the packaging vector, to change the behaviour of the virus if you wish. And second the lenti-virus vector, to produce whatever you want it to! Once the packaging cells made your viruses, containing your lenti-vector, the virus get secreted into the media, which the packaging cells are in so you have to extract the media, congaing the virus, and concentrate the virus using centrifugation. Once you got the virus then you can use it to transform the (target) cells you wish.
For the lab based procedure of how you make the virus and what equipments you use and how to concentrate the virus then please see this link, although its a little technical. In this case, the packaging vector is fuGENE 6 and the lenti-vector or just plasmids of interests are listed (please not that I do not endorse any products mentioned here and I'm just using it as an example).
Now for making the packaging plasmid (making the virus), you often use the genetic materials from a virus and change it through a procedure called polymerase chain reaction (PCR). Same goes for the lenti-vector/plasmid as they are derived from somewhere and then change through time using PCR and restriction digests, which is an equivalent of genetic material cut and paste, to make the vectors and products of interest. Once all is done the the virus can infect the target cells and effect it based on its designed function (defined by the two vectors I described).
If the above response does not answer you question, since it is currently very broad, please make further clarification to the question so that I can modify my response accordingly.

Consider this as a summary of the previous answers. Also, I am elaborating more on how to make self-sustaining mutated viruses
Points to consider before you think about working with viruses:-

Viruses are pathogenic and the biologist working on them faces a risk of infection. Viral work is always carried out in a protected environment at high biosafety levels.
Viruses need a host to survive. You need to culture host cells or use a live organism to propagate the virus. Generally one goes for the latter only if cell culture methods are unfeasible.
Almost all viruses have a very small genome (which can be replicated very fast), that can be either DNA or RNA. The genome has only very few essential genes that are responsible for the virus capsid (external shell) formation and early replication; most other factors required for the propagation are hijacked from the host.

Having identified and obtained a suitable host, one can proceed to genetic manipulation. The lentiviral vectors that Bez described are basically partial viruses. One part codes for the capsid and cannot make active viruses by itself whereas the other holds the genes for replicative function. So in a way the lentiviral vectors are disarmed viruses that are used as molecular biology tools. But what you are looking for is different.
To modify a virus you need to make mutations in its genome. Once you have identified what mutations are to be made then as previously mentioned, PCR can be used to incorporate them. This technique is slightly different from a usual PCR (not in principle, though) and is called site-directed mutagenesis. For ease it is always better to clone (fix) the viral genome in a plasmid (circular DNA that can be propagated in a usual lab bacteria- E.Coli). After mutating the viral genome, you can excise it from the plasmid. Note that PCR is done with DNA. For RNA viruses you need to convert its genome into a DNA sequence before you go for site-directed mutagenesis. Conventional technique would be to reverse-transcribe the viral RNA. But nowadays chemical DNA synthesis has become quite easy and you can synthesize entire viral genome in a "test-tube".
Having done this, we proceed to the trickiest part: How to get this genome to form an active virus?
Some viruses, as mentioned before use RNA as their genome (poliovirus, retroviruses, common-cold virus etc) while some use DNA (chickenpox, smallpox, herpes etc). The mutagenesis, however, is performed on the DNA. For DNA viruses, introduction of the viral DNA into the host cell, using the conventional transfection methods, might work. For certain RNA viruses like poliovirus this DNA has to be transcribed to RNA. This can be done using a technique called in-vitro transcription (IVT) and the RNA product can be introduced inside the cell. IVT wont work well for long RNAs. In such cases you can use the cell itself to make the RNA instead of doing it in-vitro. Use a plasmid that can transcribe a DNA sequence inside a host cell- this is fairly common and almost all molecular bio labs will have such plasmids. Transfect this plasmid inside the host cell and it will make viral RNA, which in-turn will make active viruses.
Retroviruses work slightly different from other RNA viruses. They have an RNA genome that they convert to a DNA. This DNA gets integrated in the host genome and keeps producing viruses. To make a retroviral DNA integrate you need an enzyme encoded in the virus- integrase. You can clone integrase separately and co-transfect it with the viral genomic DNA.
A couple of final points to consider:

Some viruses such as retroviruses can mutate very fast naturally, because of their error prone replication. They may lose the incorporated mutation unless the mutation provides them a tactical advantage (this is true for all organisms).
I share with many others this opinion that that bioterrorism should not be glamorized. So take care to present it well :)

I would not start from so bottom as Bez in making viruses.
This is very very long project.
It is much less cumbersome task to consider modifying virus, since it already occurs passively in real life.
I would choose equipment based on the characteristics of the virus.
I would start to develop equipment needed for the specific project, since there is no ready solution for this kind of task.
The equipment can be targeted to

actively changing virus (ss(-) and ss(+) RNA virus)
virus not changing so much (here you have to think how you ignite the point mutation and why).

I would use iPS stem cells to as an target but to get this far is very very long process still.
I would focus on antigen presentation - again very many fine regulation factors in Interferons etc should be considered in the special viral case - note that the interferon research is now in an active phase but early.
Interferons are specific so specific parts of the equipment should exists to detect them - for instance, IFN-gamma.
Viruses are generally extremely difficult to control - shortly existing in one form.
You can imagine how difficult they become after editing them real life.
So the plan would be first to understand some easy virus and its early stages in the replication.
You can actually choose a virus that undergoes continuously point mutations (drift mutation) like influenza virus.
However, I would pick something that is not so changing (not RNA virus).
There is no good equipment to do regular analysis of the changes in the influenza virus.
It always requires much work to recognize which genome part has changed and how much internationally.
The vaccines are made based on reports from many countries about their influenza virus statuses and their genomes.
Some simple DNA virus with very slow but fixed point mutations in time so you have time to research them and you can estimate when the next change is going to be.
It would be also useful if you know which part of the virus is going to change (particular plasmid).
This makes the research much more manageable.
Sufficient time-series analysis and group of Mathematicians are also needed to understand different data from different stages.
Actually, your task is extremely broad.


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Theoretically, what technique would one use to modify a virus so that it only affected a subset of the population?
I'm writing a novel and i would like to know some of the equipment and techniques involved with modifying a virus.
Is it feasible for a virus to be engineered to only affect certain people? It doesn't have to be possible, only sound like i know what i'm talking about. I have been trying to research the subject but nothing i have found will tell me the basics of what is involved with virus modification.
Thanks.

just read http://en.wikipedia.org/wiki/Genetically_modified_virus

What you need to have is a unique entry road for the virus into the body which is specific for your subgroup to be infected. This might be a mutated surface receptor of cells lets say in the respiratory system. The virus can only dock to the mutated version to enter the cells. Changing a virus is some very basic molecular biology combined with cell culture. It will require experience and some specialized lab equipment (to work sterile for example) but can definitely be done.

Just for humour: Are you trying to make a virus that will kill only some selected people that you want to exterminate?? :P

@WYSIWYG Well, his novel certainly looks to be along those lines. :D

Yes, it is possible and probably you won't need many literary artifices to make it work.
Essentially viruses are what is technically called "obligate intracellular parasites".
Parasites because they cannot grow by themselves, they need a host cell from which they "steal" the intracellular machinery to replicate; intracellular because they grow inside cells; and obligate because they cannot reproduce outside their target cell.
Now, each virus has its "favourite cell" to infect. For instance HIV targets a type of lymphocytes (cells of the immune system), other viruses may only target bacteria (these are called bacteriophages) and so on.
How is this specificity achieved? Well, to put it simply, viruses "anchor" to specific proteins (or other molecules) that are sitting on the membrane of their target cells and that allows them to go in. If a cell does not have that specific protein, then the virus cannot infect it.
So, in your story, maybe the target population will have a mutation in their genome that will modify a certain protein. You could then (fictionally) construct a virus that specifically targets cells expressing that protein and you're set!
The virus construction part is just standard molecular biology, really.
A few things to read:
http://en.wikipedia.org/wiki/Genetic_engineering
http://en.wikipedia.org/wiki/Genetically_modified_virus
http://en.wikipedia.org/wiki/Viruses <--this explains a lot

@OP.. you should note that the small differences in these membrane proteins may not be great enough to abolish virus binding. There are few individuals with mutations which will abolish or enhance virus adsorption, although, it is unlikely (considering present statistics) that an entire population is either immune/highly susceptible to a virus. You can claim that a hypothetical virus infects a certain population which has lets say a certain HLA type.

Humor again. In your novel you can name the evil scientist as Chris Nico :P

Also - there would be a strong selection for mutant viruses which gained the ability to recognise the receptor variant in the immune population.

@WYSIWYG Hehehe, nice idea. :-)

@WYSIWYG: sure, sure, but I think that for a novel one can allow a little bit of "relaxation" in how correct is the biology :)

Failed to mention the importance of a viral envelope

@buzrw.. viral envelope is where the adsorption proteins are present. Everything that a virus has is encoded in its genome.. what has anyone missed here?

Please explain if you leave a negative vote so I can improve the answer. I can surely go into much nitty gritty detail about virology, but that will probably not help the OP, but rather confuse him...

@nico that will probably not help the OP, but rather confuse him... OP seems to be a girl :P

@WYSIWYG: oops, sorry kelw, I was lazy enough not to scroll up to the top ;)

Virus is a non-living but infectious structure consisting of a nucleic acid core and envelope covering. The envelope is what determines target specificity.
If you are genetically engineering, lets say a retrovirus (which if you are writing a sci-fi book this is probably the type of virus you are wanting to write about, for many reasons) you would want to use peices of DNA that code for integrated expression cassettes for viral Gag, Pol, and Env proteins, all of which are required in trans to make virus.
These DNA's would be mixed and then put into a living mammalian cell (what we cell biologists call a packaging cell). This packaging cell line transcribes and translates the 3 cassettes and builds the virus.
The gag gene encodes internal structural proteins, pol encodes reverse transcriptase
and integrase, and the env gene encodes the viral envelope protein, which
resides on the viral surface and facilitates infection of target cell by
direct interaction with cell type-specific receptors; thus the host range of the virus is determined by the design of the envelope proetin.
As for some example envelopes, the amphotropic envelope protein has historically been the protein of choice for infection of human and other mammalian cell lines. The 10A1 envelope protein has also been used due to its increased versatility relative to the amphotropic
protein.

As @WYSIWYG mentioned, I think HLA type is probably the best way to claim specificity.  Then the glycoprotein (fusion protein probably) on the virus fits only in an exact MHC class II molecule.  If you want to hit some valid heavy science jargon, I recommend saying the virus was made with recombineering, using a bacterial artificial chromosome (BAC), with a florescent marker to make the scientist's life easier (mush harder to work with viruses without nice markers).
Here is a methods paper that describes that exactly, and has the advantage of of a free published protocol as well.
My problem with this method (using an HLA type to target) is that if you're targeting MHC Class II, it's going to be hard to kill the victim quickly.  Kill off all the cells would give a person AIDS, but not necessarily lead to a quick death.  Targeting MHC Class I could get around this, but then you're not targeting specific cells (could be nerves, could be skin cells), and the person would probably mount a pretty good immune response.  You'd probably have to hit the person with a pretty high dose to be sure you were infecting the cells you wanted to kill.
If you're willing to allow a two-step process, I think the more targeted approach would be to create an inducible latent virus.  Take one that commonly infects humans like CMV, and modify it so that it was only induced out of latent infection by a specific trigger (tagged food for example).  Then further modify it so that it generates a highly toxic protein when it comes out of latency, like botulinum, that will both kill the person very quickly and have the possible appearance of something natural.  If you use food is a trigger, then health workers would eventually figure out were all these people were eating and accuse them of food poising with botulism.  Whether that can help your character in the plot, I don't know.
Back to the creation of the virus, I would still use the method above, though it's important to note that botulinum is a select agent, and that proper BSL would be a serious concern.  Have a hard time imagining it going down in someone's garage without them killing themselves.  But if the person known how/has materials for gene synthesis (many, many labs do), then acquisition is just a question of making the gene for the published botulinum sequence.
It does occur to me that I might not should even post this based on it's ability to work...feel free to vote/comment to close if that is conciseness.

I would pick some virus that infects all people but then engineer it to not work properly on some specific host cells, e.g. some allele somehow preventing transcription of some key viral protein sort of like RNAi..


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Why do oncogenes show genetic dominance?
As we know that tumor suppressor gene causes cancer only when both the alleles are recessive in nature.But in case of oncogenes if only one allele is dominant it can cause cancer.Why in case of oncogenes to become a cause of cancer both allele aren't recessive?

A tumor suppressor is an essential gene that regulates the cell cycle at different checkpoints. If one allele is lost due to a mutation then the function of that gene can be carried out by the other allele (There might be a less expression of that gene because of copy number reduction but it is not necessary in all cases- cases where there are feedback controls).
An oncogene is a gene that promotes cell division. Different kinds of mutations will have different kinds of effect.

Mutation leading to loss/reduction of function: Nothing is likely to happen unless both alleles are affected.
Mutation leading to hyperactivity: In this case one rogue allele will always remain active leading to uncontrolled growth stimulation.

So, it is the second type of mutation that you are referring to as in the case of Ras.
Note that any mutation leading to formation of a toxic or hyperactive protein (rogue allele), will show genetic dominance. Also see the case of Huntington's disease.


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Is there any use of CO₂ in human body?
We all know CO₂ as a waste product of metabolism . Does CO₂ have any helpful role , apart from having a role in pH of blood ?

Before I restrict the answer to human metabolism, I recon it is important to mention that
CO2 is the source of the carbon atoms of glucose in photosynthesis (in the Calvin cycle). [In photosynthesis CO2 is 'fixed'].
Even with the above restriction, I am certain I  cannnot do justice to every helpful aspect of CO2 in mammalian metabolism, and I'll restrict myself to just one area that came to mind on reading your question: the requirement for carbon dioxide (in the form of bicarbonate) for fatty acid biosynthesis (FAS) and, in a bit more general sense, mammalian/bacterial biotin-dependent carboxylation reactions. Depeding on other contributions, I might be able to extend this a bit later.
Salih Wakil showed that CO2 is an absolute requiement for fatty acid biosynthesis, but carbon atoms from CO2 do not appear in the fatty acid product.
We now know that FAS begins with the carboxylation of acetyl-CoA to malonyl-CoA, catalyzed by the enzyme acetyl-CoA carboxylase. Acetyl-CoA, ATP and bicarbonate are the substrates for this enzyme, and malonyl-CoA is a key product. One of the many interesting properties of this enzyme is that it contains biotin, which (in this case) may be considered a carrier of 'active' CO2.
This explains the requriement for carbon dioxide but why no carbon from CO2 in the final product?
It is now known that in subsequent FAS reactions, a derivative of malonyl-CoA condenses with a derivative of acetyl-CoA (I am simplifying here) to give a four-carbon compound with loss of CO2.
Thus, carbon dioxide (in the form of bicarbonate) is an obligate requiement for mammalian fatty acid biosynthesis, but no CO2-derived carbon is incorporated into fatty acids.
Carbon dioxide is also required for oxaloacetate formation from pyruvate. This reaction may be though of a method of 'filling up' a key Krebs Cycle intermediate (a  so-called anapleurotic reaction).  The enzyme here is pyruvate carboxylase and the substrates for the reaction are pyruvate, bicarbonate and ATP, with oxaloacetate being a key product.  This enzyme also contains biotin and (like acetyl CoA carboxylase), CO2 becomes covalently bound to biotin during the reaction cycle.
Pyruvate-CoA carboxylase was discovered by Harland.G Wood and C. Werkman in bacteria (See here for a good reference on the early work on pyruvate carboxylase). Its discovery was very controversial because at the time it was thought that animal/bacterial cells could not 'fix' CO2; that is it was though that CO2 is only 'fixed' in photosynthesis.  This discovery disproved that piece of dogmatism.
A third enzyme that requires CO2  as substrate (in the form of bicarbonate) is propionyl-CoA carboxylase.  This enzyme occurs in mitochondria and functions in odd-chain fatty acid metabolism.  It also contains biotin.
I have concentrated on some biochemical aspects of your question.  The three enzymes mentioned, acety-CoA carboxylase, pyruvate carboxylase and propionyl-CoA carboxylase all require CO2 in the form of bicarbonate as substrate, all contain biotin, and (as far as I am aware) all play very central roles in mammalian metabolism.  (They also all require ATP as substrate).
Of the many interesting aspects of biotin, I'll mention just one.  Egg white contains a protein, avidin, which binds biotin very, very tightly.  In fact the biotin-avidin interaction is one of the strongest non-covalent interactions known.  As far as I am aware, no-one knows the function of avidin in egg white.  Some bacteria contain a similar  (but evolutionarily unrelated) protein called streptavidin. No one knows the function of steptavidin either (again, as far as I am aware).
The original Wood & Werkman paper: was published in the the Biochemical Journal in 1936
The utilisation of CO2 in the dissimilation of glycerol by the propionic acid bacteria.
Harland Goff Wood and Chester Hamlin Werkman.
Biochemical Journal, Volume 30, January 1936, pp 48-53

"acety-CoA carboxylase, pyruvate carboxylase and propionyl-CoA carboxylase all require CO2 in the form of bicarbonate" - None of the three uses H2CO2 from the blood made by carbonic anhidrase?

Some additional points about role of bicarbonate (which is directly formed from carbon dioxide as described by TomD):

Helps is neutralizing the acidic chyme when it enters intestine.
Formation of shells in invertebrates and eggshells in birds and reptiles. Shells are formed by deposition of calcite (calcium carbonate) which primarily happens by increased bicarbonate and calcium secretion.
Bicarbonate is also important for chloride transport (Anion exchange). In RBCs it happens through Band3

To add my 2 cents worth: Breathing rate and depth is regulated by chemoreceptors in the medulla in the brainstem. These chemoreceptors primarily respond to pH of the blood, but the pH is for an important part determined by the CO2/HCO3- equilibrium as explained by @TomD. Essentially it is the increase in CO2 that is sensed by the medulla and which increases breathing frequency and the depth of inhalation. See this web page about respiratory control.

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Why can CO₂ be transported dissolved in plasma?
Is it because CO2 is more soluble in water or has it got to do with the alkaline pH of plasma ?I here mean only aqueous CO2 transport from body cells to lungs.

can you cite some support for this?  offhand i would think that CO2 is more soluable in acid - it forms bicarbonate carbonic acid.

At what level do you mean? Are you talking about transporting from a source to a sink? CO2 is soluble in pure water, and as atmospheric partial pressures of CO2 are going to be lower than physiologic levels, any reversible buffering is just going to aid in transporting CO2 "downhill".

By Dissolved state do you mean just the aqueous $\ce{CO2}$ molecules or those that are in form of $\ce{H2CO3}$ and $\ce{HCO3-}$ (free or associated) also?

Edited the question

Solubility of gases is affected by the chemical nature of the gas. Acidic oxides dissolve in water readily because they react to form acids. The high pH can keep the acid dissociated thereby pulling the gas-acid equilibrium towards acid. CO2 is more soluble, in general, than nitrogen and oxygen because it is polar (however it lacks net dipole moment)

The bulk of CO2 is transported as bicarbonate/carbonic acid.  The conversion between CO2 and carbonic acid is catalyzed by carbonic anhydrase in red blood cells, otherwise the conversion would be very slow. The bicarbonate is then shuttled out of the RBCs and into the blood plasma. The CO2 (gas) in blood plasma accounts for <10% of CO2 transport, and the solubility isn't that much different from that in water.
Source: Guyton and Hall Textbook on Medical Physiology

about the same amount of CO2 is transported by hemoglobin...

Hemoglobin actually doesn't carry very much CO2, as it doesn't have a dedicated spot to carry it.  There is a binding site on the protein, but its purpose is to facilitate the release of extra oxygen to metabolically active tissues.

... in fact only 10% of it!  see wikipedia: Hemoglobin.

Haemoglobin cannot bind CO2. It is not a good ligand for metal co-ordination complexes. However carbon monoxide is a strong ligand and can form carbonyls with metals, which accounts for its toxicity.

@shigeta - I thought you were saying hemoglobin carries as much CO2 as bicarbonate transport does...my mistake!

@WYSIWYG Hemoglobin does have a CO2 binding site - its not the haem site though.  LMGTFY: http://en.wikipedia.org/wiki/Hemoglobin#Binding_for_ligands_other_than_oxygen


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Primer heterodimer problem
I design my primers in Primer3PLUS and analyze them in Oligoanalyzer3.1, A big problem that I have this is that I got very nice output in NCBI-Primer BLAST for their specificity but a very negative ΔG for self or hetrodimer even under -7 or-13. is it possible use them for PCR by adding DMSO or Formamide? what other way may be helpful?

Is it possible for you to provide the primer sequences. Sometimes it may not really matter because the primer dimer may not be extended by the polymerase. What is the Tm of primer-template and primer-primer pairs. You may not need DMSO at all.


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Why aren't introns found on the ends of pre-RNA?
We recently learned in genetics class that exons always cap the ends of nascent RNA. I have been trying to figure out the reason why introns can't instead be found on the ends instead of exons. The end introns would still have their 5' and 3' splice sites, and assuming the splicing machinery functions correctly, these introns would be removed. The only thing I could imagine occurring is inappropriate nucleophilic attack of the end 3' hydroxy group at the end 5' phosphate leading to a single circular RNA. However, in a normal situation where exons are at the ends, if introns in an RNA are  all removed simultaneously than it is possible that the free 3' hydroxy group of say intron 2 could attack the 5' end of another intron leading to inappropriate cleavage of the intervening exon so having exons at the ends does not solve that problem. I don't think my explanation is correct, any ideas?

You should revise splicing mechanisms. Splicing requires that the intron be flanked by exons. There can be nucleolytic clipping of the ends- as in case of tRNAs, but they are not generally referred to as introns (though one technically can).

I was unclear..I was asking why introns are not found before the 1st exon and after the last.

There are untranslated regions of mRNA flanking the exons, even after splicing. These are creatively called the 5' and 3' untranslated regions. These regions help regulate translation and mRNA stability. I've never heard of it, but maybe there are cases where RNA gets cut out from between an exon and an untranslated region.

Neither pre-mRNA or mature mRNA begin with exons, they begin with the 5'UTR. Are you asking why the sequence after the 5'UTR is always an exon? Or are you asking why there can't be introns before the 5'UTR?

@user137 (and Armatus) UTRs are exons, some of them even contain introns and are spliced just like coding exons.

@terdon So the definition of exon is the RNA that isn't removed, rather than RNA that becomes translated into protein?

@user137 exactly. Being an exon has nothing whatsoever to do with being a coding exon. You even have transcripts that don't code for protein at all but that contain introns regardless.

RNA splicing refers to a certain kind of RNA processing mechanism which leads to the excision and exclusion of some regions of the primary transcript. You should note that this is not the only method by which such a thing can happen; Endo-ribonucleases can clip the ends of the transcript and this happens in the case of tRNA-processing. But as "splicing" happens it is essential that the excised region be in the interior of the transcript. See the figure.

RNA splicing begins with assembly of helper proteins at the intron/exon borders. These splicing factors act as beacons to guide small nuclear ribo proteins to form a splicing machine, called the spliceosome. These animation is showing this happening in real time.
see>
http://education-portal.com/academy/lesson/rna-splicing-of-introns-exons-and-other-forms-of-rna-processing.html#lesson
http://www.youtube.com/watch?v=FVuAwBGw_pQ
http://www.sumanasinc.com/webcontent/animations/content/mRNAsplicing.html


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chimeric sequences
I understand that chimeric sequence identification is done in results of sequencing projects to remove them and improve the quality of the output. I am unsure as to how they show up during sequencing. Any explanation is appreciated.

Do you mean chimeric sequences that are artifacts of the sequencing process or actual bona fide chimeric transcripts that are present in vivo?

Yes, but you're contradicting yourself. Some chimeric sequences are very real and exist in vivo. Others are artifacts, mistakes introduced by the sequencing process. Which ones are you asking about?

Chimeric sequences show up in sequencing projects a lot and you always have to watch for them. They show up a lot for a couple of reasons.
Firstly, sequencers are not perfect and generate sequences with errors.  Also they produce a lot of data but often not quite enough.  There are usually thin spots in the sequence assembly - regions which are not covered very well.
When a sequencing error coincides with a gap in the sequencing, the two ends of a sequence alignment can align to two unrelated or distant segments of sequence, creating an alignment assembly which has two unrelated portions - a chimera.
This is especially the case in EST and RnaSeq runs where long scaffold sequences and higher coverage might not help as much. It does have an impact in Chromosomal sequencing as well.  There's some interest in how often contaminating DNA get included into sequencing output.

My understanding of chimeric sequences is that they are produced as the result of inserting two different cDNAs (usually from different species) into a backbone such as pUAST to make a protein that is partly from one species and partly from another species. Sometimes you want to do this because for example the ligand for a receptor in lets say Drosophila is very difficult to produce but the ligand for the mammalian receptor is easily available so what scientists do is that they attach the human cDNA corresponding to the extracellular side of the receptor to the Drosophila intercellular portion of the Drosophila receptor. Now you can intracellularly activate a Drosophila receptor using a human ligand for a receptor. Now I have never seen/heard of chimeric in vivo sequences and that just doesn't seem possible but what I imagine can happen when viewing sequencing data for a species that are not fully sequences is that the search engines says a particular sequence is from a different species that you have sequenced. This is because the database will try to find the closest match to the sequence. NCBI BLAST for example can do this but usually it gives you a percentage sequence matching/probability. Otherwise I'm not sure what you mean by the word sequencing projects. Could you provide an example/reference?


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Most well studied termite species or a species that I could use to compare termite genes for functional annotation
I am working with termites and I have a set of genes that I would like to compare with a species similar to termites so that I could elucidate its function. I am looking for a species that is similar to what Drosophila Melanogaster is to bees where to elucidate the functions of bee genes, it is compared to genes in D. melanogaster. Or how most worm genes is compared to genes in C. elegans. Similarly, if there is a well studied termite species, I could work with that.
The ultimate goal is to create a gene network with termite genes, hopefully on STRING.

Apparently, the most closely related insect to termites is cockroaches. Interesting article I found on the subject. However, that still didn't help because cockroach genes are not included in the STRING database.

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How do you define a gene list?
So I wrote in a chapter that I will be checking for publications with gene lists in them. I got a comment asking "How would you define a gene list and what criteria did I use". I know that gene lists are usually generated by microarray studies, NGS analysis etc but what is the best way to define a gene list?
I am running blank except maybe say that its a list of genes.
EDIT: "I defined a gene list as a list of genes generated as a result of a microarray analysis or a next generation sequencing study." Sounds good?

Correct me if I am wrong, but from your bio I suspect your background is in the numerate rather than the biological sciences. If so that would explain why your question "lacks context" (@Michael_A) or "is unclear" in SE Biology terms. A "gene list" means almost nothing, even with the rider "generated by microarray or NGS analysis". Just as a list of cars is almost meaningless, even if quaified by "generated by perusing newspapers". You must define the purpose of the experiments. Genes expressed in growing animal cells, after heat shock, after hormone treatment, in liver etc.

@David My work was to essentially get the number of publications with gene lists in them so as to make an argument that there are such a lot of lists being produced with potentially no follow up analysis being done on the majority of these lists generated in different studies. That is why I could not provide biological context to the question. Do not jump the gun, downvote and then vote to close before I get a chance to respond to your comment David.

The comment explained the down and close votes which were (and are) based solely on the question. I was not obliged to do this but felt it might be of use.

@David Of course you are not obliged, its just good practice. I hope I was able to explain the context of the question to your satisfaction. Have a good day.

The comment seems useful as your current definition of a gene list lacks context.

How would you define a gene list?

There are many different kinds of gene list. Specifying gene lists from microarray and next-generation sequencing provides some context but both technologies are used to analyse many different kinds of DNA and RNA samples. Define the molecules that are being referenced by the gene lists.
Defining DNA or RNA isn't sufficient as each gene list is compiled to perform a research task. Genomic projects may provide lists of genes that were sequenced or mutated or contained single nucleotide polymorphisms. An RNA transcript project may create lists of genes where transcription was occurring in a tissue or whose RNA transcripts were influenced by experimental factors or whose splicing was altered. Most publications also include multiple gene lists and some of those will include rows that were removed following data evaluation. Define the kind of lists that you are collecting.
There's value in defining your search criteria well. It allows you to communicate your work to others and it can provide focus to your search efforts.

What criteria did I use?

This was mostly answered above. I would also consider including some rules for the publications that you will search for gene lists.

I don't think this is an answer to a biological question, it is an explanation why the question is meaningless as it stands. Better as a comment.

On the contrary, I think your answer has given me some idea on how to address the comment and I thank you for that.

@David, Biology Stack Exchange is for people studying biology at any level. Questions are from students, academics and active researchers in biology and closely related fields. @The last Word appears to belong to that group and I think the answer provides a biological context to the question. Comments are not for answering questions.

You misunderstand me. My point is that the question is not clear, not that it is not biological.


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Is the complement system a part of innate or adaptive immunity
I've been reading about the complement system, as part of the human immune system. The complement system is introduced as part of the article on innate immunity on Wikipedia. This classification makes obvious sense in the case of the alternative pathway, which is obviously not dependent on any specific pathogen.
However, I'm confused about whether this is an appropriate classification for the classical pathway (and, therefore, the system writ large) since the classical pathway is activated by antigen:antibody complexes and only by certain antibody isotypes (IgG and IgM). It is, therefore, to some extent pathogen specific and it is also, clearly, activated by and dependent upon the humoral immune response (generally classed as part of adaptive immunity).
So, in short, is it best to classify the complement system as part of the innate immunity (and, if so, why is that?), or would it be better to restrict ourselves to the observation that it is, to a greater or lesser extent, part of both types of immunity?

The innate mechanism can be classified as 1. Physiological barrier
2. Cells of innate
3 .Chemical mediators such as interleukin, complement, interferone. The alternative complement is however effective in innate immunity because it's not dependent on antibody.

Yes, the complement system is part of the innate immune system. It can be activated by the:

classical pathway (activated through bound IgM and IgG molecules but
also by DNA, collagen (both are usually not available freely outside
of cells) and c-reactive protein)
lectin pathway (activation by binding of mannose through the mannose
binding lectin on the cell surface)
alternative pathway (activation by the constant hydrolysis of the
complement component 3 (or C3) in an antibody independent way)

My guess here would be, that the classical activation via antibodies is evolutionary younger than the other two possibilities which act more directly on bacteria and do not depend on the availability of specific (at least to some degree) antibodies. The Wikipedia article on the complement system is pretty extensive.

Just to underline that last point from @Chris - the signature property of the complement system is the use of proteins with reactive thioester groups to covalently tag cells, and this is very ancient. The plugging together of antibodies and the complement system is certainly a relatively recent innovation. The OP raises what is really a semantic point. There are also interactions between cellular immunity and humoral immunity, but it is still useful to think of these as separate processes with an interface.

Its also a matter of time: Generation and maturation of highly specific antibodies takes some time (the peak of new antibodies after an immunization comes after 14 days) while the innate immune system can kick in instantaneous. Its reaction is less specific and can probably be overcome by some bacteria, but its still pretty effective first line of defense.


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For people who work in microbiology labs, what software do you use to manage your strains?
It's just a small microbiology lab that currently records everything on paper, and there's quite few mutants as well. Is Excel commonly used for this sort of thing? Or is there a better software to manage a lab?
Thanks for any help

check out benchling for constructs... is that the sort of software you mean?

@shigeta not exactly, although this is pretty cool. But we're just looking for something offline, to keep track of all the different strains in a fridge, and when they mutate to somehow show that the mutants are related

What I think you're looking for is normally called an LIMS (Laboratory Inventory Management System), and I've never used a good one.  Seriously, decided to spend the effort to build one in house because everything else we tried was horrible.

That's why most people who can afford it write their own LIMS systems - few labs ever do things the same to use a 'generic' LIMS.

@AtlLED Thanks, and yeah I've been looking around for the past couple days and it seems like most free LIMS are pretty terrible. And when you say you built one, did you end up designing it with SQL? Or did you use an Access database (or something like that)?

In my old lab we started with a .Net solution and then moved to an SQL/web based one. Now my lab uses a very similar modification of the SQL one. I want to add that my experience with LIMS that you pay for "semi-out-of-the-box", ie Nautilus, are also crap.

I would go for StrainControl Laboratory Manager. Works perfect and covers all needs of a lab. Do not go for all the "free" stuff since they rely on a active sponsor and your data is never safe.
StrainControl is free for 3 months and if you want to continue use it you simply purchase the Admin password and all your data is saved.


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Do Archaea have membrane-bound organelles?
From Campbell Ch. 6 Intro to the Cell,
Which of the following statements concerning bacteria and archaea cells is correct?
A) Archaea cells contain small membrane-enclosed organelles; bacteria do not.
B) Archaea cells contain a membrane-bound nucleus; bacteria do not.
C) DNA is present in both archaea cells and bacteria cells.
D) DNA is present in the mitochondria of both bacteria and archaea cells.
(A) is correct. My logic was that Archaea and Bacteria were originally from the same family as they are prokaryotes with membrane-less organelles. Is this thinking correct? If not, where am I wrong?

Surely the answer is C.

A) Archaea cells contain small membrane-enclosed organelles; bacteria do not.

FALSE. As you said, Archaea and Bacteria are prokaryotes: that don't have any nucleus nor membrane-bound organelles.
B) Archaea cells contain a membrane-bound nucleus; bacteria do not.

FALSE. See comment above.
C) DNA is present in both archaea cells and bacteria cells.

TRUE. Apart from some kind of viruses, all living organisms* have DNA as the support of their genome. It confirms that other choices are false.
D) DNA is present in the mitochondria of both bacteria and archaea cells.

FALSE. See comment for answer A: neither of them have mitochondria.
More info: Archaea on Wikipedia
(*) Viruses aren't always considered living organisms.


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Why does BLAST reduce word size for short proteins?
I'm using BLAST to identify a short protein (BLASTp). If I check the short query then the word size reduces from 3 to 2. However the search will then be less reliable right? Because reducing the word size increases the chance of finding matches? So my instinct would be to raise the word size to almost the whole length of the query, because with a short query you want to search really specific to reduce output results, so apparently I'm missing something.
So I hope someone can explain me why reducing the word size from 3 to 2 is better for short proteins while using BLASTp

As a general rule, playing with the word size is a question of finding the right balance between specificity and sensitivity. I guess that's why they said that 'A good rule of thumb is that the query length must be at least twice the Word size. ' on a blast FAQ site. see here

No, the search won't be less reliable. It will only be more sensitive, more capable of finding matches. To understand this, you need to understand how the BLAST algorithm works, what the word size means.
When you use a word size of $N$, BLAST starts by looking for a match of length $N$ between your query and target sequences. If such a match is found, BLAST then attempts to extend the match as far as possible. So, for example, consider these two sequences:
> query
CRKKL
> target
CRAKL

As you can see, they are quite similar:
query           CRKKL
target          CRAKL
                ** **

Now, what happens if you try to find the target sequence with BLAST using the query sequence and a word size of 2 ($N=2$)? BLAST will take the first
$N$ characters of the query and try to match them against the target:
CR
CR
**

It will then try to extend:
CRK
CRA
**

It will find a gap and apply the gap penalty, but continue matching since the next characters match1, thereby increasing the overall score of the alignment:
CRKK
CRAK
** *

And so on and so forth. BLAST starts by matching the first $N$-sized word and then attempts to extend the alignment.
Now, what if we were using $N=3$?
CRK
CRA
**

Because the word size is now 3, we need at least three matching residues to match in order to attempt to extend the alignment. Since there is no 3-letter match, the target is missed.
So, decreasing the word size is better for finding small protein matches because it can use shorter matching sequences as an alignment seed.
As a general rule, playing with the word size is a question of finding the right balance between specificity and sensitivity. Decreasing the word size helps you find more matches (increases sensitivity) but it will also find more divergent sequences (decrease specificity). Increasing the word size will reduce the number of matches (decrease sensitivity) because you need a longer perfect match to start extending the alignment, but will increase specificity for the same reason.
If you raise the word size to something close to the size of the query, you will only find almost exact matches. That might be what you want to do and it is what algorithms like BLAT which are designed to find near exact matches (for example, mapping a sequence to the genome it came from) do. Usually, however, we want less than perfect matches since we are looking for homologous sequences and not the exact same query. In such cases, we will decrease the word size for smaller proteins to increase our chances of finding homologs.

1 This is a bit of a simplification. The rules for extending alignments are a more complex but it serves to illustrate the point.

If I understood correctly: If you want an almost exact match, the word size can be almost as high as the query length. However if you need to identify homologs (so assuming there isn't an exact match), you can better lower the word size to find more matches? @terdon

@RickBeeloo more or less, yes. Having a large word size means that you will need a large section of the target to be identical to the query in order to find that target. A smaller word size makes the search more sensitive.

But why does lowering the word size using a blastn reduces sensitivity and lowering the word size using protein blast does exactly the opposite? Thankyou for explaining everything by the way ,helps me al lot.  @terdon

@RickBeeloo the SE sites are for questions and answers and don't lend themselves to discussions. Ping me in chat if you want more details. That said, unless I'm mistaken, reducing the word size would also increase sensitivity for blastn.

Sorry I made a mistake you are right @terdon, increasing word size also increases sensitivity for nucleotide searches


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Are prosauropods ancestors of all sauropods?
My daughter, while reading a book about dinosaurs, asked me if prosauropods are ancestors of all sauropods. Are they? From the name ("pro-sauropods"), I guess that they are, but am I right?

Welcome to Biology.SE! Your daughter asks interesting questions!
The question is debated. It is currently mostly thought that sauropods and pro-sauropods are sister lineages and therefore, one does not contain the other. In other words, the pro-sauropods are no more the ancestors of the sauropods than were the mammals are the dogs are the ancestors to the cats.
One of the most updated source of information for phylogenetic questions of the kind is tolweb.org. You should have a look. Here is the page for the Sauropodomorpha (which contains the sauropods and the pro-sauropods). You have a nice list of reference on this page including some from Sereno, who is the author who first defined the pro-sauropods.
I quickly sought through the literature. It seems indeed that all phylogenetic analysis were based on phenotypic comparisons and not on genetic comparisons. Citing from wikipedia:

Evidence against sauropod ancestry within Prosauropoda comes from the fact that prosauropods had a smaller outer toe on their hind feet than the sauropods. Many maintain that it is easier for digits to be reduced or lost during evolution than the reverse, however there is no evidence for this. The lengthening, or gaining of extra digits is common in marine reptiles, and within the theropods digit lengthening occurred at least once. Therefore, using this as evidence against ancestral prosauropods is questionable.

To be fair, genetic analysis of dinosaurs would be very very hard, phenotypic comparisons are probably the best we can ever do.


text:
Comparative Genomics
Are orthologs and paralogs examples of conserved genes? Orthologs are the genes or DNA that is present in 2 different species, having once been present in a common ancestor. It comes about by a speciation event. Paralogs come about by gene duplication events.
So, would we characterize these genes as conserved genes?

Relevant discussion on orthologs vs paralogs: What is the difference between orthologs, paralogs and homologs?

Could not fit in a comment...
To my understanding, paralogs and orthologs refers, as you said, to the relative isolation of gene copy to the isolation of populations (and eventually species).
Gene conservation on the other hand refers to the variability of a given gene along many species. If a gene does not show any variance along many species, than we say that it is a conserved gene.
Eventually, gene duplication may allow for neo-functionalisation, sub-functionalisation or loss yielding to variance among this gene copy. Aside the philosophical problem of what is the identity of the gene, there is no relationships between the concepts of orthologs versus paralogs and gene duplication.

Yes, of course they are conserved. Conservation is basically a measure of sequence identity. It can be used to describe the relationship between both paralogs (genes created by a duplication event) and orthologs (genes created by a speciaton event). Any type of homology relationship can be described in terms of the conservation (sequence similarity) between the genes investigated.
Even entire genomes can be described as more or less conserved.


text:
Explain a gene network to a first year undergrad
I have an adjacency matrix with list of genes connected to each other which signifies the gene network. How do you get this information that one gene is connected to other in the first place. Is it that you do a microarray analysis and find genes that are upregulated and downregulated and assume that all the genes that are upregulated, regulate each other. Kindly explain.
P.S The microarray example is what I assumed. Doesn't mean that it should be the way that a gene network is deduced. My network is an undirected one.

As for unsupervised networks, you could start by explain some rudimentary network inference methods. Here is a good review https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3956069/.

There is no single answer, because networks (or graphs, as they are called in discrete mathematics) are flexible tools that can be used to model all sorts of relationships between genes, transcripts, proteins, or other entities in biology. (And networks are useful models in many other disciplines too, like sociology.) Depending on the type of network you're considering, there are various experimental methods for determining connections. I give only a couple of examples below. For general information on networks as abstract models, look into graph theory.
Gene regulatory networks
A gene regulatory network is a directed graph where one gene (A) regulates another (B). In this case, the connections between genes are directional and can be represented by arrows A $\rightarrow$ B. Depending on exactly how you define "regulation", a connection A $\rightarrow$ B can mean different things, for example:

Gene A encodes a transcription factor that binds to gene B. In this case, evidence for A $\rightarrow$ B comes from assays of proteins binding to DNA, such as chromatin immunoprecipitation (ChIP). Large collections of such data are available in databases like Transfac.
Expression of gene A causes regulation of gene B, by any mechanism (possibly indirectly). In this case, data for an interaction can come from experiments where gene A is induced (forcibly expressed) or suppressed/deleted and the resulting changes in other genes are measured, for example by microarrays or RNA sequencing. A famous early example of this is the "Rosetta" data set on yeast deletion mutants.

Inference of gene regulatory networks is a large and complicated topic that I cannot cover here. It depends on many factors, such as how you model the time dimension (do you have steady state or transient data), and how you parameterize the network to model expression data quantitatively. The review suggested by @CMosychuk looks like a good place to start.
Coexpression networks
This type of network represents coexpression between genes (or more accurately, between mRNAs or proteins). This is typically a representation of pairwise correlations between genes across some set of conditions, so the data source can be any collection of mRNA or protein level expression data. (Here is one example.) Because correlations are symmetric, connections in this type of network have no direction, and can be represented simply as a link A$-$B (not an arrow). Partial correlations are sometimes used to filter out indirect associations, but still these networks contain no causality information, and should not be confused with the directed type.
Protein-protein interaction networks
These are undirected network models where a link A$-$B means that two proteins interact physically. Data supporting such connections come from various biochemical assays for protein interaction, such as the two-hybrid assay or immunoprecipitation. There are large databases collecting protein-protein interaction data that can be used to build these network models, for example BioGRID.
There are many other types of networks, but this is already a long answer :) As you can see, it's important to be clear on what type of network you are working with. Often the data you have available will determine what network model is suitable --- for example, if you have only a collection of unrelated transcriptome profiles and no causality information, a coexpression network might be the best model.


text:
Gene networks for different tissues?
I currently work on gene networks and specifically, I analyze the brain gene regulatory network of an insect to understand its sexual behaviour. During a recent presentation, I got asked this question which I just couldn't really tackle in a good manner. The question was why do I study the brain gene network to understand sexual activity when I should be studying the gene network of a sexual organ, for eg: the ovary. I got out saying that since the brain decides behaviour, it would be much better to study the brain GRN. However, I got confused and would like to know if different tissue or organs in the same organism have different gene networks? Any idea regarding the theory is welcomed.

Of course different tissues have different gene expression - I'd expect that isn't something at all new to you so I'm wondering why you are asking the question? Your response to that somewhat bizarre question seems fine to me, maybe the question asker was trying to lead you into a discussion of how sex organs also affect gene expression in the brain, e.g. via hormone production.

Check out this heart development paper. What's striking is different programs for varying progenitor cells within the same tissue, and the presence of core elements from other cell types or tissues such as GATA3, working together to perform unrelated functions. Cell have the capacity to express the same gene network, but how they're regulated differs on a number of variables.


text:
Is blunt end repair and A-tailing necessary when adaptors can be custom made?
I'm planning on creating a RADseq library, which naturally involves digesting genomic DNA following P1 adaptor ligation. I've read a few protocols that require any over-hangs resulting from restriction enzyme activity (e.g MspI or Nlaiii) need to be repaired (blunt-end repair) followed by adding a single A nucleotide at the end so as to make the DNA fragments "sticky". But is this really necessary? Wouldn't it be more efficient to custom make P1 adaptors so that they have a complimentary 3 or 4 bp overhang specific to the restriction enzyme used instead?
What I want to ask is what are the practical advantages of having a single nucleotide overhang vs. 3 or 4 nucleotides?
Thanks in advance.


text:
How to transform snail shells into a fertilizer?
I heard that the chemical structure of the snail shell has elements that help in waste water treatment and in some cases as a fertilizer?
What is the process used to render snail shells into fertilizer and how effective is the derived fertilizer compared his regular peers on the market ?

Snail shells are composed largely of calcium, which is often used as fertilizer. As for wastewater treatment, I've heard about shells in general being used, mostly for their absorbent properties. I found this paper, which isn't long & might provide a bit more detail.
Hope that helps!

May I ask about the quality of the fertilizer derived from the shells and their effectiveness compared to other fertilizers on the market ?


text:
Does any one know which species of insect is this one?
I found this insect, in multiple zones of Imbabura - Ecuador. https://en.wikipedia.org/wiki/Imbabura_Province
Sorry for not having something to scale with, but it's about 15 cm long.

Another picture here:

In general, it helps identification if you add the location where on earth you found the animal.

I edited the question @Marzipanherz. It is very important!

That is a male dobsonfly. I know this is a male because it has long mandibles which are used in mating. Female dobsonflies have short mandibles. larval dobsonflies are called hellgramites,and it really hurts a lot when they bite you.Look here https://en.wikipedia.org/wiki/Dobsonfly or here entnemdept.ufl.edu/creatures/misc/eastern_dobsonfly.htm

Yes, Megaloptera, Corydalidae, Corydalus cornutus

Just in case, does anyone know its name in Spanish?

I edited the question @peter . So I should suppose that the second photograph is a female, right?

I found the Spanish name. A dobonsfly is a "Mosca de pescar oriental"

I didn't see the second picture. when I saw the first picture, I thought "I know what that is!" and just jumped at it. The second picture is a female, the long mandibles of the male are used in mating.

Not Corydalus cornutus. That species is only found in Eastern North America. There are several other Corydalus species found in that part of South America. It would require an expert in them to get a more specific ID. Note that the pictures are of two different insects as well. The one on top is a male, the bottom one a female (as the earlier answer noted, females have shorter, more robust and powerful mandibles, though males and females can each draw blood with a nip (personal experience)).


text:
Biological significance of network parameters
I am currently working on networks and I have calculated various parameters for the network like diameter, average path length, average eccentricity, radiality etc. Could someone guide me to some articles I could read as to what biological significance these parameters hold with regard to a biological network (gene regulatory network). Example, what does a small diameter, radiality etc say with regard to the biological property of the network. On research I could only find one article which could be of some help. Thanks
Edit: I understand that this question has been identified as being too broad but all I require are links to articles that could perhaps guide me to an appropriate solution. Perhaps, the answer can be limited to how does a large network affect a radiality value affect a biological network?
Edit2: Its a cluster from a bigger network, is bipartite in nature, consisting of Transcription factors and genes with a size of 361 nodes. My aim is to check if the clusters are all different from each other and determine if there are significant differences between each cluster. The question was all about what biological inferences can be drawn from network parameters like diameter, radiality etc. For example, a network with low diameter means that network information is passed faster between even the furthermost nodes meaning pathways in that network could have genes with functions that require quick actions, say genes that govern sensory perceptions like reflex actions.

You will have to limit this to what sort of question you are trying to answer with that network. You might want to use all of these features or none of them. You should also explain what size of network this is and whether it was built using one gene, many, the entire genome or what.


text:
What's this insect?
Found on my indoor egg plant. I also have aphids, spider mites, and psyllids on it, and am hoping it's a predator like a ladybug larva but the colours are wrong. It's about 6 mm long. Found in New Zealand.

We can't identify anything if you don't give us your exact location. "China" is not specific enough, "southern Beijing city" is fine.

The photo isn't very good, but I'm almost sure that's a hemipteran (a planthopper, leafhoppter, depends on the type of hemipteran, I can't say). And it seems to be a nymph (a imature individual).

As Lfppfs said it seems to be a nymph of planthopper, Dictyonissus griphus.

This website has more pictures. If you are interested you can find fully formed (matured) Dictyonissus griphus.

Nice picture, looks very much like mine.

It usually has a long fibrous white tail, as you might have seen from the rest of the pictures I linked. I wonder what might have happened to its tail.