text:
Is it true that there is a spider that eats parasites from caterpillars
I think I once saw a video of a caterpillar that could get infected by a parasite, and could die of that, unless a specific kind of spider would eat the parasite, and so once the caterpillar is infected it goes looking for that spider. I can't find that video anymore though, nor any reference on this, so I'm beginning to doubt myself. Does this behaviour really exist?

Oddly enough it is a bit difficult to find good field studies where the diet of spiders was studied.  I have a feeling it's a hard thing to get funding for.  Luckily some do exist.
Peucetia viridans has been shown to eat from the Chrysididae family and Lepidoptera order, but I didn't find an explicit statement that it ate the larvae out of the caterpillar.  Likewise Oxyopes globifer was found to have eaten from the Braconidae family and Lepidotera.
At this point you might be wondering why I'm looking for spiders that have been shown to eat both parasitoids (Chrysididae and Braconidae) and caterpillars (Lepidotera).  It my assumption that in the scenario you describe a spider that would normal eat ether the caterpillar or the larvae would be just as happy to eat them both if it was lucky enough to find them.
I could find one example where it seems wolf spiders under the right conditions might seek out larvae, and I found a fun photo of a wolf spider eating larvae (though not the kind in the study).
I never saw the video you were talking about, and I too could not find it.  It is not unreasonable to assume that an opportunistic spider wouldn't just take the opportunity to feed on both, or that it might find the larvae more tasty and just eat them.  I've not found a spider seeking caterpillar as of yet.

That's no fun photo! Thanks for the search. Actually the way I remember it it was actually even more crazy than the spider looking for the caterpillar; it was the caterpillar looking for the spider. It was a rather small spider, couldn't eat the caterpillar, but the larvae was a good meal.

@JasperKennis Again I would be very interested if someone could pull that up. Under the right pressure I could imagine such behavior evolving, but I am unaware and couldn't find an instance where it is true.  It might be worth noting that plenty of insects/spiders eat pray that are larger than they are.


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How can I re-format my DNA motifs' position weight matrices?
I am working with a set of DNA motifs that are predicted as potential regulatory motifs (e.g. transcription factor binding sites).
The motifs belong to several species, and I wanted to cluster these motifs via their Position Weight Matrices (PWMs) (also known as PSSMs) to collapse similar motifs together into groups.
There is a tool called MATLIGN (website here) that does what I need, but their required format for the PWMs are different to what I have, they claim:

"Matrices must be in the frequency matrix format (only integer numbers
  are acceptable)"

The problem is that my PWM matrices do not have integer numbers but decimals instead. e.g.:
     A        C        G        T
1    0.000000 1.000000 0.000000 0.000000
2    1.000000 0.000000 0.000000 0.000000
3    0.000000 0.000000 1.000000 0.000000
4    0.000000 0.421755 0.000000 0.578245
5    0.289407 0.000000 0.282556 0.428038

In other words, instead of the decimal values I have in my matrix I need to have integer counts. Could anybody suggest what I can do? Would I need to create artificial "pseudo-counts"?

Could it be so simple that they want counts of nucleotide occurances (the frequency) instead of proportions (e.g. your row 5 as (using n=60): 17 0 17 26)? Where do your numbers come from - I assume you have counts as raw data to calculate the proportions? Mind you, I have no experiance with these particular methods at all.

Thank you @fileunderwater for your comment. The problem is that the raw data is not available to me, what I have are the high level outputs the program had generated. I presume the whole integer counts are required by this software since proportions remain constant no matter how large the total.

ok, well then you have a problem, since there is no way of knowing the margin of error of the proportions. However, to get counts these proportions should just be multiplied by the number of binding sites included in the study. Don't you have that info (e.g. the number of sequnces that have been analysed)?

brilliant! I DO! you should make an answer of that! Thank you

Why not just multiply everything by 10? The PWM will still be correct since its values are relative to each other, you just make 1.00 into 10 and 0.28 into 28 etc.

Hi @terdon I was very tempted to do that before fileunderwater's answer came about. It turns out he was right, I eventually found in my dataset there was a "mysterious" variable called "nsites". After reading the small print of the docs, nsites is the number I should be multiplying by, since it is the number of DNA regions the motif was made under

Yes, his solution is cleaner but I doubt there will be any difference. Remember that PWMs are relative so multiplying by anything should be fine really.

@terdon As I wrote, I'm not familiar with this program/methods, but I assumed that the counts were used in the analysis to determine what confidence you can have in the proportions (i.e. more confidence in 33% from 40/120 than 3/9). But you might be correct that it doesn't make a difference in this case.

I'm not familiar with this program either but PWMs in general are always relative. What you get is a value indicating how often a particular residue is found a t a given position. Multiplying with an arbitrary value shouldn't affect the result in any way, as long as you multiple all values. Basically 1 means you always have that residue at that position. If you multiply by say 100, you can treat them as percentages. But yes, the implementations could vary depending on what you're feeding them to.

So what you need is basically your data expressed as counts instead of proportions. Even if you do not have the matrix of counts as raw data, these proportions only needs to be multiplied by the total number of binding sites used in the study (e.g. the number of sequences that have been analysed) to get the counts (since proportion = count/total number of binding sites). You should have that information somewhere.
@hello_there_andy: indeed there was this missing piece of information available to me, it came in the form of a variable called nsites which equates to the total number of DNA sites that the PWM was generated from.

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Where does the 'C' in exhaled CO₂ mostly come from?
When a human being exhales CO₂, what is, by the numbers, the main source of carbon atoms exiting the body in this way? I mean what class of cells, or which tissues are the biggest on a pie chart of where carbon atoms breathed out in the form of CO₂ molecules came from?

Duh, I just realized it's probably mostly from leftovers after the sugars that you eat are burned for energy. I've also heard that broken-down fat from weight-losers gets breathed out. Is that at all true?

yes, the CO2 is the product of various metabolic processes. I can expand if you want...

CO2 is a product of Cellular Respiration, which generally takes Glucose and molecular Oxygen to produce Carbon Dioxide, water, heat, and allows ADP to be regenerated into ATP (or other various oxidation reactions). The Carbon comes from wherever the acetyl-CoA used in the Citric Acid Cycle came from - either carboyhydrates or fatty-acids (saturated carbon chains).
Simplified reaction:   C6H12O6 (s) + 6 O2 (g) → 6 CO2 (g) + 6 H2O (l) + heat
So, you are correct. CO2 transferring out of the lungs is mostly the result of burning sugars (or fats) for energy (the regeneration of ADP/GDP with respect to human biology).
To that end, the tissues that produce the most CO2 will be the cell-types which constantly require energy. Nominally, muscle tissues.
Per your comment, broken down fat, or rather, the process of Fatty-Acid Catabolism, results in the production of acetyl-CoA, which is a primary player in the Citric-Acid Cycle. The Citric Acid Cycle, which you should recognize as the Cycle that Pyruvate - the end result of Glycolysis (the breakdown of Glucose into 2x 3-Carbon Pyruvates) - also goes into after being converted into acetyl-CoA by Pyruvate Dehydrogenase.
The sum of all reactions in the citric acid cycle is:
Acetyl-CoA + 3 NAD+ + Q + GDP + Pi + 2 H2O → CoA-SH + 3 NADH + 3 H+ + QH2 + GTP + 2 CO2
So, for a basic breakdown with respect to CO2:

Carbohydrates (Sugars, Starches) → Glucose → Pyruvate + ATP + NADH
Pyruvate → Acetyl-CoA
Lipids (fats) → Lipolysis → Acetyl-CoA
Acetyl-CoA + ... + H20 → ... + CO2

In the resting state it's the brain that is responsible for the largest proportion of cellular respiration: estimates vary but are usually in the 20-25% range. This is because even at rest the nervous system is working hard to maintain the ion gradients that are essential for propagation of action potentials.

At rest, the main sources of CO2 are the brain, liver and heart.
The original questions seems to me to be asking for information about which tissues or organs are responsible for producing most of the exhaled CO2. As other answers have mentioned, CO2 production by cells reflects the amount of oxidative metabolism that is being carried out. This means that we can answer the question by simply asking - which tissues/organs are responsible for consuming the most O2?
There are many sources of information about this, but the most succinct statement that I have found is here:

The average human body of 139 lb (63 kg) consumes 250 ml of O2 each minute. The major single-organ oxygen consumers are the liver, brain, and heart (consuming 20.4%, 18.4%, and 11.6%, respectively), while the sum total of all the body's skeletal muscles consume about 20%. In addition, the kidneys use up about 7.2%, and the skin uses 4.8%. The rest of the body consumes the remaining 17.6% of the oxygen. Oxygen use can also be measured per 100 gm of an organ to indicate concentrations of use; as such, heart usage is highest, followed by the kidneys, then the brain, and then the liver. During exercise, the biochemical oxygen demand increases for active tissues including the heart and skeletal muscles.

Other sources are in broad agreement with this. Note however that these are values at rest. As the quotation states, during active exercise the skeletal muscle will become the major source of CO2.

The chemical formula for glucose is C6H12O6. When the body needs energy, the glucose molecule is broken down to give CO2 and water:
$C_6H_{12}O_6 + 6O_2 => 6CO_2 + 6H_2O$
Therefore, I think "C" comes mostly from glucose molecules.

The two main chemical processes in the human body that generate carbon dioxide (CO2) are:

Basal metabolic process of CO2 (CO2m) produced by the combustion of sugar in organs and tissues of the body.
Bacterial decay processes occurring as a result of activity of the microbial fauna in the colon. This forms CO2 (CO2c), H2, CH4 and higher hydrocarbons, NH3, H2S and other mercaptans.

The total level of carbon dioxide in the blood (CO2b) is therefore the sum of the metabolic (CO2m) and carbon dioxide arising in the large bowel (CO2c). In certain circumstances CO2c arising in the colon may be resorb into the bloodstream.

Could you add a citation or two to provide readers of your answers the chance to do further reading? It is considered a prerequisite for valid answers at Biology.SE to include references.  I type-edited your answer a bit. Welcome to Bio.SE and thanks for your contribution! +1

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text:
Link between macro lncRNA and DNA looping
I was wondering if anybody knows some publication about macro lncRNA (very long unspliced RNAs) or more generally a transcribed RNA that may lead to cis-DNA looping of genomic regions overlapped by the (macro) lncRNA transcript ?
Thanks

I didn't actually understand the phenomenon that you are describing. You mean a long RNA binds to different regions of DNA (in cis) causing them to come together?

It's more the act of transcription of a long RNA that may lead to bring distant chromosome regions closer by the act of 3D DNA conformation.

I don't think the act of transcription, per-se will bring DNA domains together. It would open up the chromatin. However the "act of transcription" has been said to precede recruitment of Polycomb/Trithorax complexes and these in turn can recruit chromatin remodellers/enhancers etc.

Thanks. Do you have in mind a recent paper talking about it ?

I haven't read a recent paper on this. I was doing a project on Polycomb in my UG and that is when I read this in an annualreviews article. It has been 7 years since then. I am sure more research must have been done on this. But in general this concept itself is quite dubious. I can only suggest you directions to look at. Another thing that you can look for is pervasive transcription.


text:
Are all single-celled organisms Bacteria?
I read that "Bacteria are one-celled organisms that can multiply by division", are all one-celled organisms bacteria or are there any more narrow definitions?

You mean more narrow definition for bacteria?

No, many unicellular organisms are not bacteria. Examples include (but certainly not limited to); some fungi, chlorella algae, and archaea.
Bacteria are one of three domains in the classification of life. You can find more about the bacteria domain at the wikipedia page (It's a long and complex history which is hard to summarise here) and about the domains here. This last defines bacteria loosely consisting of "prokaryotic cells possessing primarily diacyl glycerol (DAG) diester lipids in their membranes and bacterial rRNA, no nuclear membrane, traditionally classified as bacteria."
The composition of lipids in their membrane (DAG-esters) differentiates them from another major class of prokaryotes — Archaea, which have isoprenoid lipids in their membranes.
Initially Archaea was called Archaebacteria. Because of significant differences, including the membrane composition, they are now grouped into a different kingdom.

No, as @rg255 already mentioned, bacteria are one of the main kingdoms of life:

The Bacteria and Archaea are all unicellular organisms (though there are strange Archea like the Pyrodictium genus that are borderline multicellular). The Eukaryota include all plants, fungi and animals but there are also unicellular Eukaryotes. For example, Paremecium is a unicellular animal, brewer's yeast (S. cerevisiae) is a unicellular fungus and Chlorella is a unicellular plant.
In other words, all bacteria are unicellular but not all unicellular organisms are bacteria.


text:
How is gene expression estimated?
I'm reading this fantastic article on estimating body time: Molecular-timetable methods for detection of body
time and rhythm disorders from single-time-point
genome-wide expression profiles and one of the things that is not very clear to me is how the researchers estimated which genes are expressed and which ones are not:

Total RNA was prepared by using Trizol reagent (GIBCOBRL). cDNA
  synthesis and cRNA labeling reactions were performed as described (5).
  Affymetrix high- density oligonucleotide arrays (Murine Genome Array
  U74A, Version 1.0, measuring 9,977 independent transcripts) were
  hybridized, stained, and washed according to the Technical Manual
  (Affymetrix). Affymetrix software was used to deter- mine the average
  difference (AD) between perfectly matched probes and
  single-base-pair-mismatched probes. The AD of each probe was then
  scaled globally so that the total AD of each microarray was equal. The
  resulting AD values reflect the abundance of a given mRNA relative to
  the total RNA popu- lation and were used in all subsequent analyses

I'm not sure if I'm reading this correctly - did the researchers look at all RNA available in the cells and calculated the levels of messenger RNA produced by expressed genes? if not, how can the level of expression of a gene be estimated?

The technique described here is called microarray. Your question has given me an opportunity to put forth one of my opinions about certain problems of gene expression studies.
Gene expression is a measure of the activity of any gene. If the gene performs its activity in the form of a protein, then its expression should be a measure of the protein. If a gene makes a non-coding RNA then its expression is a measure of the RNA concentration.
[You can omit the cases of post-translational modification because of signal transduction. They are highly expressed and transiently but frequently used. ]
Like your example there are many studies which use mRNA concentration as a proxy for protein activity. This proxy works in many cases because transcriptional gene regulation is more frequently used mechanism for imparting stable changes. But the best strategy would always be to measure the proteins also.
Apart from microarray there are several techniques to measure RNA concentration:

RNA sequencing (high throughput)
Real-Time PCR (medium throughput)
Northern Blotting (Low throughput, semi-quantitative)

Many techniques exist for measuring proteins also:

Mass spectrometry (high throughput)
ELISA (Low throughput, quantitative)
Western blotting (Low throughput, semi-quantitative)

Usually the "proxy method" is used because protein quantification is comparatively more difficult. Antibody based techniques like ELISA and Western blotting have problems of cross comparison of proteins because of the variability of the antibody binding efficiency.

when you want to focus on just one gene, qPCR should work better. Microarrays are best for total transcriptome evaluation.

yeah.. one or countable number of genes..

Unfortunately I don't remember the details but I recently saw a talk in a conference where it was demonstrated that mRNA levels don't really correlate with protein levels. I mean, we've always kind of known this but the numbers shown were shocking (less than 50%, perhaps as low as 30). I will try and get a hold of a reference and post back.

Wow, just found an article from 1998 stating that in yeast "We found that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data." And yet here we are, still using such data...

@terdon It varies dependent upon case, for many cases there is a relationship, but its hard to say apriori.  This is difficult if you have a large number of probe sets of interest.    As a rule of thumb, qPCR panels go up to a couple of score of genes or so and then they become difficult.

@shigeta I know, I just have this graph from the conference I mentioned in my head (cannot find it) where the did a transcriptome level analysis and the correlation was pathetic. I'll find it somewhere it was a keystone meeting in Heidelberg can't be that hard to find.

@terdon.. it is not always necessary but there are several evidences that protein levels dont correlate with mRNA levels..

@leonardo: hey mass spec is not that traditional :P

@terdon i've also seen other graphs too -a notable one would have been a graph with many points in George Church's class at HMS I saw once.  Given the state of things, a reference and a reading of the work would be useful.  My recollection was that the correlation was esp at poor mRNA concentrations and that the overall slope was 3 for humans.  Overall correlation wasn't great but it wasn't 0 either.  As always, anyone who expects a solid rule in biology for such things is looking to be disappointed ...

Ok I found and wrote up some of the information around my back and forth with @terdon.  hope some find it relevant.

@leonardo: you are very right, nowadays that the microarray fad is gone not many journals would accept a study showing ONLY microarray data, without any further validation. Of course, the solution is to jump on the current fad, RNAseq :D

@leonardo: Can you clarify what you mean by MS being highly sensitive? It's my understanding that one problem with MS that you only get reliable (any) readouts for the most abundant of proteins in your sample, no?

@SteveLianoglou: As I understand MS is sensitive in the sense that it can detect minute quantities but the big problem is the data interpretation

Supplementary information from the Comments from the first answer:
I have perhaps found @terdon's reference?  Not sure if this is it, but by measuring transcription events in individual cells, Taniguchi et al. certainly make the case that there is no correlation between protein and mRNA levels.
However microarray data (and most rnaSeq and qPCR experiments) are ensemble measurements; they measure the average mRNA concentration in a sample of millions of cells.  In the aggregate, the paper also says that in the aggregate, the average mRNA correlates to the average protein product concentration.  See this nice writeup in the OmeSpeak blog.
Overall, what is happening microscopically: translation is a somewhat stochastic process in the individual cell and events have to be modeled explicitly.  Biology in the aggregate (averaged case in a cell population) is often what we have to work with; single cell techniques are quite arduous.  (run a protein gel on a single cell!).  I think there is room for both sorts of information when investigating biology; certainly publication of work measured on more than one cell at a time will continue for some time.
All the work cited here is in E coli, but in Eukaryotes one assumes that this is not going to be any simpler.

gene expression noise is also a variable feature.. in some gene networks, the noise is low whereas in others it is high..


text:
Why do cells have an average 'life span'
I've heard of Henrietta Lacks. As a result of a genetic mutation, her cells never died. I've heard/read that overtime, our cells stop multiplying as much, (as an effect of aging). Why? Why do we age? Why do cells eventually die? What causes our bodies to degenerate? It is encoded for in our genes? If we treated our bodies in the highest regard, accounted for accurate diet and sleep, with the introduction of genetic engineering, could everlasting life be possible?

Henrietta Lacks had cervical cancer, and her cancerous cells somehow survived in culture (I don't know if this was due to proper handling by the lab staff or otherwise).

@Rustyn Yes, the possibility of immortality in the sense of everlasting of the body is a more and more accurate hypothesis

We refer to the number of times the cells of an organism can possibly divide as the Hayflick limit for that organism. The Hayflick limit serves as a theoretical life span, because telomeres (on the ends of chromosomes) get slightly shorter with each round of division, until they are gone completely. Telomeres are put on the ends of chromosomes by the enzyme telomerase, which is abundant in infants (who are growing and undergoing rapid mitotic divisions) but bodily abundance of the enzyme quickly diminishes with age. Without telomeres, our actual chromosomes would shorten in length during each round of division -- essentially, this is what happens after the telomeres are eroded away at in the later years of life. The Hayflick limit for humans is given to be 120 years -- with perfect self-care, 120 years of life is possible.

Nice answer. Do you have a reference for the 120 years claim?

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text:
Books on population or evolutionary genetics?
I have recently been involved in collaborations that require me to model the population genetics of eukaryotic populations. I fear I may either be "re-inventing the wheel" or making conceptual mistakes (e.g. simplifying assumptions) in many of the techniques and decisions so far.

I would very much appreciate recommendations of books about population/evolutionary genetics or micro evolution to deal with these fears. Preferable criteria are:

Intuitively introduces key concepts.
Emphasis on modelling with examples of problems and their solutions.
Relatively short (I'm planning to read from cover to cover).

Great suggestions so far, and the edits by @fileunderwater

TL;DR
I'd recommend Population Genetics: A Concise Guide (Gillespie) for an introduction to population/evolutionary genetics (thanks AGS for highlighting this big miss of mine on the first version of my answer).
I'd recommend A Biologist's guide to mathematical modelling in evolution and ecology (Otto and Day) if you want to ensure your knowledge in mathematics by learning their application to evolutionary biology.
General Entry Books to Population Genetics
There are several books that offer an introduction to population genetics. I read Principles of Population Genetics (Hartl & Clarke). I appreciated it but if I were you I think I would rather try Elements of population genetics (Charlesworth) or Population Genetics (Hamilton). There is also Genetics of Populations (Hedrick). I would tend to think that this last book presents lots of empirical population genetics data and doesn't take as much focus as the others in theoretical concepts (but I might be wrong). Gillespie's book Population Genetics: A Concise Guide is a classic. It is short, very easy to follow and pleasant to read. Gillespie's book might eventually be a little bit outdated but I would still highly recommend it.
Emphasis on Analytical Modelling
A Biologist's guide to mathematical modelling in evolution and ecology (Otto and Day) is a very good and very accessible book. It makes a good review about all subjects that are usually taught to first year students in Biology such as linear algebra for example. It is highly accessible and in the meantime it goes pretty far as it ends up talking about the application of diffusion equation in population genetics (Kimura's work among others). This book presents some important models in population genetics but as it aims to provide the tools for mathematical modelling in ecology and evolution it may under-considerate some fields of ecology and evolutionary biology. For example, the book does not talk about population structure nor about evolutionary game theory and there is little about Coalescent theory.
Other books treating specific subjects within population genetics
Coalescent Theory: an Introduction (John Wakeley) is a good book. I haven't read it completely for both time issues and because the math are a bit complicated for me. Coalescent theory offers a very important set of mathematical tools in evolutionary biology.
There's also Mathematical population genetics (Ewens). I am currently reading it. It is definitely not an introductory book and it really doesn't cover much of the most common fields in population genetics.
If you are particularly interested in age-structured population, Evolution in age-structured populations (Charlesworth) is a very good book.
Modeling evolution (Roff) offers some discussion on how to mathematically define fitness from phenotypic traits. While it is interesting I would not counsel you to buy it. Moreover, all the mathematics are quite basic and it aims to explain how to perform mathematical modelling with R which is to my opinion not essential to learn as other languages make a better job at dealing with math (Mathematica for example).
Evolutionary Conservation Biology (Ferrière, Couvet and Dieckmann) is a very good book of conservation and conservation genetics. It develop some mathematical models that are of special interest to conservation of populations and communities.
Ecology, Genetics and Evolution in Metapopulations (Hanski and Gaggiotti) is a book that may interest you as well. However it focuses much more on ecology than the other ones I cited above. Note: I haven't read it entirely.
If you are interested in kin selection and level of selection, you might want to have a look at Major Transitions In Evolution (Maynard Smith and Szathmary) which is a classic (I have not read it though) or The Major Transitions in Evolution Revisited (Calcott and Sterelny) who encompass the opinion of many authors on the subject. Evolutionary Dynamics: Exploring the Equations of Life (Nowak) is also of interest esp. for those interested in epidemiology. Finally, you might want to have a look at the extremely well written and easy to read books by Dawkins such as The extended phenotype (Dawkins) for example. The Dawkins book are very popular and very very introductory. It offers more a way to think than the actual science behind evolutionary biology.

my savior, cheers

Sorry for this late response. I am studying evolution these days and thought of learning the basics from Hartl and Clarke. As I was reading, I realized that the book doesn't give full proofs/derivations to any formulae. I find Kimura's papers quite difficult to read. Which book of this would you suggest me for a complete understanding of the mathematical aspects of different models/formulae? For e.g., I want clear derivations of Kimura's equations.

@WYSIWYG Kimura wrote a lot of equations. Which one are you having a hard time to understand? If you're having a hard time with diffusion equations and kolmogorov equations, you might want to have a look at any intro math course to diffusion equation. A Biologist's guide to mathematical modelling in evolution and ecology (Otto and Day) (linked in the post) gives some easy introduction to diffusion equations but does not enters into the details of its derivations. Hope that helps

See my new question.

I saw it (and upvoted it) after writing my comment. I am not able to answer it though. Asking on math.SE could be a good idea.

@Remi.b's list is excellent, but it should also include Gillespie's Population Genetics: A Concise Guide.

You've written this anser two years ago. Since that I kept the note that I had to read this book. I finally did it and could make an appropriate comment in my answer. It is a very good book I agree. Thanks!

Wow, I knew that Gillespie simulations work wonders for gene-circuit engineering. Wonders it does work, for modelling stochastic dynamics at multiple organisational scales in Biology then I guess. Cheers. http://www.sciencedirect.com/science/article/pii/S2001037014000403

I personally like the Primer on Population Biology by Wilson and Bossert. For a book that is almost 45 years old, it holds up pretty well. One of the best things about this book is that they provide examples and then walk through the solutions step by step. Once in a while it gets a bit too mathematical for this Biologist, but overall, I find it readable and informative.
I think this book fits all of your criteria very closely.

Not relatively short, but I'm going to repeat a recommendation I just made in another thread. Population Genetics and Microevolutionary Theory by Alan Templeton covers many of the topics listed above, and is heavy on the self-learning of various population structure statistics, with examples. It is an introductory textbook with for people with some statistical background (though it includes a statistical appendix as well). There is quite a bit of discussion of Bayesian inference and other modeling methods as well.


text:
How quickly is antibiotic resistance lost?
I would imagine the bacterial genome is highly conserved and limited in its space, but maybe I am wrong.
If you were to take a strain of antibiotic resistant bacteria and kept them isolated, but fed well and so forth, how long would it take for them to lose their resistance? A year? A decade? 100 years? 1000 years? At some point it seems like that trait would disappear, but I have no feeling for how long. Please support your answer with a relevant citation.
EDIT:
My purpose is simple: I am thinking about a strategy for dealing with antibiotic resistance. If we were to ban them across the entire world (could be impossible) how long would we need to wait before they would be usable again. If it was a matter of years, then we could almost do a rotation of existing antibiotics (if we had enough) because I would rather not live in post-antiobitic world.

Is this a homework question, by any chance?

@MattDMo it is not.

Related/duplicate: Can antibiotic resistant bacteria compete with normal one in an antibiotic free environment?
related: What causes the development of antibiotic-resistant strains of bacteria?

Antibiotic resistances in bacteria is commonly encoded by extrachromosomal DNA, the plasmids. These are circular pieces of DNA, which are much smaller than the hosts genome and which replicate independently from it. See the image from the Wikipedia:

These plasmids can be transfered between different bacterial cells, which then also get resistant. Plasmids are divided between daughter cells, when the parent cell divides. One of the few exceptions seems to be Mycobacterium tuberculosis, which does not seem to carry plasmids but also develops resistances. It has been hypothesized that they contain extrachromosomal single-stranded DNA ("Does Mycobacterium tuberculosis have plasmids?")
Regarding your question: Plasmids which carry antibiotic resistances will only disappear, when the antibiotic is not seen for a while, since the cells, which don't carry it, have a growth advantage over cells who are still carriers (since they save the energy of forming the plasmid). However, these resistance plasmids are nothing new, evolutionary speaking. They appeared as a countermeasure against fungal toxins.
In the lab, bacterial strains loose plasmids within a few days, when not kept under selection pressure according to my experience. There are a few paper who looked into it:

Natural selection, infectious transfer and the existence conditions
for bacterial plasmids.
The persistence of parasitic plasmids.
The evolution of plasmid-carried antibiotic resistance

If you were to take antibiotic resistant bacteria and kept them
  isolated, but fed well and so forth, how long would it take for them
  "forget" their resistance?

It's not a matter of "forgetting".  Bacteria are resistant if their DNA is such that it gives them a biology that renders the antibiotic non-lethal.
You put a resistant bacteria in glycerol stocks, you can freeze them for years, maybe longer, and when you revive the population, and get it growing again, the resulting population will still be resistant.
Also, when we talk about bacteria, or any kind of evolution, single organisms don't change their DNA.  Populations change their proportion of different alleles.  Any allele might drift out of a population, and if the resistance-granting mutation is deleterious, natural selection might speed that along, but not all resistance-granting alleles are deleterious enough for that.  If a resistance-granting allele is survival neutral in the absence of the antibiotic, or another mutation somewhere else restores the bacterias' survivability absent antibiotic to what the sensitive genotype's fitness is, the resistance-granting allele might not drift out of the population for a long time.

I'm not talking about putting resistant bacteria in glycerol stocks and freezing them, I'm curious about keeping them multiplying in a petri dish. Finally, I use "forgetting" not in a technical sense, but a figurative.
The allele must eventually be lost, but I would like some sense of how long until it is lost.

" I'm curious about keeping them multiplying in a petri dish."  So you are talking about a population, not an individual.  If you abandon that distinction, nothing makes any sense.  "The allele must eventually be lost"  You can get strep resistance in TB through GidB deletions.  You want to believe that a population descended from a deletion mutant will forget a deletion?

So in a trillion years without the presence of any antibiotic, will that allele still be there in a population? I would be surprised if so. I don't care if it is a day, or a billion years, but I want a sense of how long. Saying it will never be lost makes no sense to me.

swbarnes2 and @sciencenewbie I'll remind you both of our community guidelines: http://biology.stackexchange.com/help/behavior

@swbarnes2 You assume too much. I am not a creationist. I believe in the theory of evolution. I don't understand why you believe it is okay to treat people like this.

Lab strains of E. coli have been in use for many decades now. They have all retained a large number of genes encoding subunits of the flagellar apparatus and the chemotaxis system which confer absolutely no advantage under normal culture conditions. I conclude from this that the selective advantage conferred by losing "unused" genes must be very weak.
Also, most antibiotic resistance is encoded on plasmids. As @Chris points out, these can be lost easily.

I would expect bacterial DNA to have some natural decay rate over generations, so I find it very interesting they do maintain these "vestigial" genes; is it possible they are actively conserved?

No.  DNA doesn't "decay".  It changes.

In general terms entropy is the decay of order. So call it what you will, the question remains of its rate. If you wrote a message that wasn't vital for the organism to survive, over time it will become corrupted unless every DNA replication is 100% efficient.

@sciencenewbie Under standard culture conditions (37C rich medium) they aren't expressed, and it is difficult to conceive of a selective advantage under conditions in which it is unnecessary to move towards nutrients. But some weak selective pressure can't be ruled out I guess.

@swbarnes2 It is called information theory and can be applied anywhere. You are not going to win me over by coming across in a hostile tone.

I agree with Alan that chromosomal traits wont get lost easily as seen with the commonly used strains. I would add a point that the likelihood of loss of a gene depends on its cost..


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Why are lions the only social cats?
We know that almost all cats are solitary.
How did the Lions (Panthera leo) end up social animals? Do we have an explanatory evolutionary path describing how the Lions became social while the rest of the felines remained solitary?
I'm not asking what general rules apply to evolution, but, rather - what evolutionary path has led to this specific outcome.
I know a bit of evolutionary game theory. No need to reiterate the obvious. I'm asking if we know the mechanism or the evolutionary pressure in this particular case.

Evolution does not have a reason. It just happens. So any question on "why such or such a thing happened", tends to be purely philosophical. You can edit your question to make it precise and non-phiosophical. For e.g. you can ask if socialization increases the survival probability of lions in the environment that they live in i.e. the savannas.

possible duplicate of If a trait would be advantageous to an organism, why hasn't it evolved?

Simple answer - it was probably beneficial to them but not other species. This is a duplicate in my opinion http://biology.stackexchange.com/questions/35532/if-a-trait-would-be-advantageous-to-an-organism-why-hasnt-it-evolved

I think http://biology.stackexchange.com/questions/35532/if-a-trait-would-be-advantageous-to-an-organism-why-hasnt-it-evolved is the reverse. That is the sort of question targeting "why haven't all predators evolved poison-slash-high speed running capability-slash-guns-slash-more nonsensical stuff?" This question seems well researched (I have a cat and, oh my, is she solitary!) and seems to make sense. For example, investigations on fossils tends to include the interpretation of geographical grouping (did they form herds?) etc. I vote to leave open. I'm not an evolutionary expert, though.

Could you elaborate more on your claim that "We know that almost all cats are solitary"?

I'm not entirely sure, but the impression I got from reading about felines was the they are mostly solitary. Although there is ample evidence that house cats can socialize: http://katzen-verstehen.at/wp-content/uploads/2013/04/social-organization-of-the-cat.pdf, I don't recall seeing material on social organization in other felines other than lions.

I guess it has to do with the failure of dogs and wolves to be able to take down large prey animals in Africa, so that left the door open for felines like lions and hyenas to collaborate and hunt for big prey animals.

@mousomer It is also very difficult to ascertain what kind of pressure would have selected a socializing trait in lions. This also tends to be speculative. I guess most grassland animals are social, even cheetahs.

Well, between @WYSIWYG and Count Ibis, now we do have a glimpse of a direction. Grassland animals form larger herds, so there is a niche for socialized predators. More questions: why are cats unsocial outside Africa? (possible answer: Homo Sapiens?). What is the mechanism forcing large herds on Grasslands? (large, open space)

Yeah, to me it seems like the perfect excuse we "scientific evolved sapiens" tend to make to masque the obvious  which is: "we-don't-know, we-can-make-a-stupid-guess-and-call-it-educated-and-if-its-made-by-some-renowned-author/scientist-it-will-be-professed-as-truth".

This is not a direct answer to your question, but I want to point out that your basic premise is partially incorrect. Other felines also form social groups. For instance, male cheetahs form coalitions (also see Cheetah outreach at http://www.cheetah.co.za/c_info.html), often for life, which generally makes them more successful in defending territories. Female feral cats also form social groups in some environments (see e.g. Natoli et al, 2007), where females sometimes co-rear kittens. There is even evidence that tigers share kills with related or unrelated individuals (see Wikipedia: Tiger for examples), and tiger home ranges can overlap in complex ways. On the other hand, lions (both males and females) are sometimes solitary, and this partially interacts with their living environment.
My point is mainly that sociality (in general or in felines in particular) is not either/or for a particular species, and other felines also show social behaviours and sometimes form groups (so sociality should be viewed as a sliding scale). Granted, lions are definitely the feline with the strongest social behaviors, and they form the largest social groups. It is therefore interesting to think about why that is the case, and what group dynamics and tradeoffs that determine the social behaviours of lions.

I think it's actually a direct answer: there is no explanation to find for a non-existent fact.

@biozic I definitely think that the Q should be rephrased and stated in less either/or terms. However, to look at the evolution of sociality in relatives of lions, as well as the costs/benefits of social behaviour in lions would still be interesting. To ask for the specific evolutionary path and its reasons is asking a lot though.

I agree with some comments that have been made on the validity of the wording used by OP. However there is a legitimate thrust to the question. What could drive Lion sociality?
Females are the base unit of lion social groups. Males are generally the nomadic sex. Male lions will try to take over a group of females by killing the current cubs and mating with the females. By having groups of females they can drive off males that are not related to their offspring.
Males are equally rewarded for banding together to defend females and to subdue larger groups of females or other bands of males. Lion packs are therefore formed by these antagonistic interaction between male and female lions. More research is needed!
http://www.sciencedirect.com/science/article/pii/000334729580157X

In brittle environments we often find very large range lands(grasslands, savanna etc) that are inhabited by mixed mega herds of numerous, large, grazing herbivores. It takes pack hunters to successfully predate upon these herds. Note that all the apex predators in the more densely forested biomes of non brittle environments are solitary hunters(Tiger, Jaguar, Bear etc). Remember that various sub species of Panthers leo once roamed from Africa, across Eurasia and into North America. There are many extinct Panthera species too.


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What physical evidence exists that shows motor proteins "walking" within a cell?
Various animations on the internet show the motor protein kinesin walking within a cell. Is this an approximation? How does this happen and (based upon what physical evidence) how do we know it "walks" like this?
https://www.youtube.com/watch?v=y-uuk4Pr2i8
https://i.sstatic.net/dXyJG.jpg
https://www.youtube.com/watch?v=tMKlPDBRJ1E

Closely related from Sceptics-SE: Is this what “happiness looks like”?.

Since you chose kinesins as an example class of motor proteins, I will also stick to them. In general, the movement mechanisms of kinesins are well studied and the general structure of kinesin proteins, that is a dimer, is known by crystallography (see Kull et al. (1996) for the structure publication).
Even before that, the movement of single kinesin molecules in discrete steps of approx. 8 nm was shown by Svoboda et al. (1993). To resolve single molecules, they used optical trapping interferometry (see this practical guide to optical trapping by the Princeton University for more detailed information). Four years later, Schnitzer and Block (1997) were able to show that that for every step of approx. 8 nm lof a kinesin molecule, one ATP is hydrolysed. Visscher et al. (1999) used molecular force clamps to study ATP and load dependent characteristics of single kinesin molecules.
So far, it appears to be that kinesins move by a 'hand-over-hand' mechanism: Yildiz et al. (2004) labelled single heads of kinesin dimer molecules with a fluorophore and found that their data are congruent with a step of approx. 17 nm followed by a step of approx. 0 nm which indicates that the two dimer hands alternate in movement.
See also the review by Hirokawa et al. (2009) for a general overview of kinesin movement.


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About the plight of Elephants and efforts to conserve them?
Poachers are only after the ivory horns right? I read this story from the New York Times ( I think) of saving a Rhinocerous by some Park Rangers and a Vet. ( forgive spelling) ; they tranquilized the Rhino and took its horn off so it wouldn't be killed. I know Rhinos need their horns so maybe a hard plastic 'prosthesis' could be put in its place. Maybe the 'prosthesis' could be colored yellow or have some markings on it so any poacher would know it's fake. Of course this could all be done for the elephant too.
Could this be a feasible way to save Elephants or Rhinos??

YOU mean their tusks right? And the Rhino horns can be so replaced also. But the non-valuable replacements would have to be marked or visibly different from 'regular' horns or tusks.

I don't think this is really answerable one way or the other.  Poachers may not look carefully enough to see what they are aiming at, or worse, the yellow horn might attract more predators.  Failing that anyone's actually studied this issue, the answers are just going to be a matter of opinion.

Rhinos and elephants don't really suffer badly from predation, there's not much that will try to take one down, so the colour wouldn't matter that much - the main issues are poaching and habitat loss.

Dehorning of rhinos has been tried with limited success. Poachers have killed dehorned rhinos anyway, either out of spite or to avoid tracking worthless prey in the future. There is the problem of anesthesia (always a risk) and the fact that rhino horns are usually not destroyed but saved in the event of decriminalization. But at least horn grows back.
Considering the strength of horn and ivory, and the force applied in their use, plastic would not be of much use to them (especially elephants with long tusks).

They are used for digging for water, salt, and roots; debarking or marking trees; and for moving trees and branches when clearing a path. When fighting, they are used to attack and defend, and to protect the trunk. - Wikipedia

To detusk elephants would be akin to declawing a lion, though much more dangerous and painful. Though this might help prevent poaching, the future of these animals lies in prevention.

So is doing nothing an option? You admit de-horning might prevent poaching , using ANESTHESIA to remove tusks.If not then to remove a tusk why not use a harmless dye to make it look ugly and not marketable.

If de-horning is painful of course forget about it , but dying the horn is still an option. Forgive my impudence , I just get tired of most of my suggestions being shot down.

I apologize again. How was I belligerent ,  I just capitalized the word anesthesia; and people have talked about removing tusks for a while and I never heard about the ineffectiveness of anethesia so I just thought I was being talked down to again.

One could also save Tigers by spraying their coat with harmless indellible ink that makes any market value poor to poachers.

In todays Globe and Mail (I bought this paper in Ontario , Canada ) there is an article  with a picture of Dr. Marius Kruger , in Kruger National Park trying to move a Rhino out of a high risk area. Trying to move these Rhinos seems like a lot of effort. Maybe just using an indellible dye or some kind of harmless dye that ruins the 'medicinal' quality of the horn might help.

Is there a harmless dye or some substance that could be 'absorbed' by the Rhino horns that would make its medicinal value worthless?

@user128932 - none of the biological dyes that I can think of would penetrate the outer layer of horn, sorry. Eventually they would wear off as well, I think, from friction.

What about injecting a dye further in?

You can't inject rhino horn. You might be able to drill into it, but that might damage the pulp or open it to infection, and there's always the risk of anesthesia. But it's good to see someone working on a way to save rhinos. Keep thinking 'outside the box'! :-)


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Detecting cancer or a genetic predisposition based on DNA sequencing
I am not by any means a biologist - so go easy.
What would be a method for determining whether or not a patient has cancer based only on a genomic sequence?
Update Thanks for the help in revising the questions.

What information is extractable once a genome has been sequenced?
Is it possible to derive whether or not a person has cancer based only on the genome which was sequenced? i.e. Are there anomalies to look out for to detect the cancer.

To make it clear: you want to know 1. What info it's possible to get from sequencing; 2. Does sequecing make any impact on the genome?

For the second question: You want to know, if its possible to make a decision if a person has a cancer only based on their DNA sequence?

@Chris - Yes i think you've hit the nail on the head.

Answering your question 2:

Is it possible to derive whether or not a person has cancer based only
  on the genome which was sequenced? i.e. Are there anomalies to look
  out for to detect the cancer.

I would say no.
The problem with mutations is that we still don't know exactly what mutations are needed for a cell to become a primary tumor cell.
There are anomalies, but we know these in fully developed tumors. I can give an example (I need to explain a bit wider for it) to show this:
The expression of genes is dependent on many different signals, some come from the outside of the cell (for example from growth factors) and they are passed down into the nucleus along so called signal transduction pathways.
For melanoma (skin cancer) mutations in some key elements of this pathways are pretty often mutated, for example we find mutations in one kinase (an enzyme that phosphorylates other proteins) in about 60% of the cases. This kinase is called Braf and it carries a mutations in amino acid 600 changing it from valine to glutamic acid (so call Braf-V600E). This makes the kinase permanently active (also when she shouldn't be activated due to a missing signal) which derugulates otherwise pretty tightly controlled gene expression.
The problem with the Braf-V600E mutation is that this is not only found in melanoma cells, but also in benign nevi. Only that these are usually senescent (meaning that they do not divide and only sit on the skin) and harmless. Most of them never transform into melanoma, but some do and here we don't know why. Obviously cells need to pick up other mutations on their way to become cancer cells and there are quite some possibilities for that.
Cancer is a pretty complex disease, which is under high selection pressure: Cells need to evade the immune system and also be able to survive, proliferate and differentiate. Whole genome sequencing has opened a door to understand cancers better and also to diagnose them better in terms of treatment, but I don't think you can really do this only on the base of a sequence, since there a too many possibilities to bring up false positive (and also negative) results.
Its possible that the Cancer genome project will change this, but I am doubtful about it.

Thank you - more than insightful it was helpful. Unfortunately the answer doesn't boast well for my research.
Again, i have a much better understanding of my issue and different ways to look at it - Thanks.

When sequencing a human's (i hope im stating this correctly) genome is
  there a difference between the genome before and after the patient is
  found to have developed some sort of cancer.

If you are asking if cancer cells have an altered genome as compared to the rest of the organism, yes, this usually is the case.

What would be a method for determining whether or not a patient has
  cancer based only on a genomic-sequence.

If you scrape some cheek cells to do DNA sequencing, you will know what the sequence is in those cheek cells, and you can figure that most of the cells in the rest of the body have that same sequence.  But if some, say, brain cells have acquired genetic errors causing them to start going haywire, that won't magically change the DNA in your cheek cells.
A genetic predisposition could be identified...if scientists had determined one.  For instance, Angelina Jolie got a double mastectomy because both her family history and her genetics strongly indicated that she would get breast cancer otherwise.

Thanks. I have a slightly better idea of what i am asking.

In some cancers its even different between different stages of the tumor cells (tumors are not homogeneous).


text:
Do we know if RHEB is more sensitive to some amino acids than other amino acids?
RHEB (Ras homolog enriched in brain) senses amino acid levels in order to recruit mTOR.
See this review describing the process of how RHEB recruits mTOR. So does RHEB have differential selectivity towards different amino acids.
We also discussed this in Matt Kaeberlein's class yesterday and I posed this question but no one could answer it (that said, Matt Kaeberlein called it a good question).

Might be a good question in the context of your class, but that doesn't make it a good question for this forum since it does not provide any of the necessary context to readers.

RHEB does not sense amino acids. See the abstract of this paper.

Activation of this pathway requires inhibition of the tumor suppressor
  complex TSC1/2. TSC2 is a GTPase-activating protein for the small
  GTPase Ras homologue enriched in brain (Rheb), GTP loading of which
  activates mTOR by a yet unidentified mechanism. The level at which
  this pathway senses the availability of amino acids is unknown but is
  suggested to be at the level of TSC2. Here, we show that amino-acid
  depletion completely blocks insulin- and TPA-induced Rheb activation.
  This indicates that amino-acid sensing occurs upstream of Rheb.
  Despite this, amino-acid depletion can still inhibit mTOR/S6 kinase
  signaling in TSC2-/- fibroblasts. Since under these conditions
  Rheb-GTP levels remain high, a second level of amino-acid sensing
  exists, affecting mTOR activity in a Rheb-independent fashion.

RHEB also doesn't have any amino-acid binding (or any small molecule binding) domain.


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Why do yeast ferment Equal sweetener
I had my students conduct a fermentation experiment manipulating sugar amounts (number of sugar packets in solution) and measuring CO₂ production via capture in a balloon and measuring circumference (very common HS lab experiment). I also had them conduct a trial with two packets of Equal sweetener. To everyone's surprise two packets of the "zero calorie" sweetener produced as much CO₂ as four packets of sugar. Can anyone shed light on why this would have occurred? Equal contains maltodextrin and dextrose in addition to the aspartame. I'm assuming that yeast are able to metabolize one or more of these substances, but I haven't been able to find a more detailed explanation.

Your sugar substrate was sucrose. Yeast cells metabolise this by secreting an enzyme, invertase, which splits the disaccharide into glucose and fructose both of which can be fermented by yeast to produce CO2.
According to this site

Equal Original (blue packaging)  is a zero calorie sweetener that contains aspartame and acesulfame potassium as its sweetening ingredients along with a bulking agent.
Equal Original PACKETS:
dextrose with maltodextrin, aspartame, acesulfame potassium

This agrees with what you say - that the sweetener that you used contained dextrose - and leaves me very confused. Dextrose is another name for glucose so how can this contain zero calories?
The answer lies in the legal definition of zero calories  = less than 5 calories per serving (presumably per package in this case.) So let's assume that by adding two packs you were adding 8 calories equivalent of glucose.
Calorie content of carbohydrate = 4 calories per gram
Two packs could contain 8 calories = 2 g glucose.
The molecular weight of glucose = 180
therefore 2 g = 2/180 moles
if completely fermented to CO2 each mole -> 6 moles CO2
12/180 moles CO2 = 0.75 litres of CO2.
I conclude that there is enough glucose in two packets of Equal to generate a reasonable amount of CO2.
Yeast cannot ferment maltodextrins. It is possible that aspartame (aspartyl-phenylalanine-methyl ester) could be metabolised, but I think the dextrose/glucose solution is the best explanation.
EDIT:
I meant to say, just to illustrate that this is a significant amount of glucose, standard rich yeast medium is 2 g glucose /100 ml (2 % w/v).
EDIT #2 My back-of-an-envelope calculation has a fundamental error in it, but luckily I am the first to spot it. If glucose is being used fermentatively, then only one third of the carbon will end up in CO2, with the remainder going to ethanol. This means 0.25 litres instead of 0.75 litres. Yeast is so oriented towards fermentation that even in the presence of oxygen the fermentative pathway will dominate.

I agree with all of this, except there is one problem with the data. (Keep in mind this was High School Bio) A packet of equal is far less mass than a packet of sucrose(since aspartame has such a high sweetness profile), and as such a packet contains a very small amount of dextrose compared to the amount of glucose/fructose in the sucrose packets. That said, there was nearly as much CO2 generated by two packets of Equal as four packets of sucrose. Granted, there is an upper limit to the yeast growth curve and metabolism, but there were higher rates as we increased from 2 to 4 packets sucrose.

Without knowing the actual contents of one pack of Equal we are at an impasse. However it is noteworthy that the formulation quoted in my answer says "Dextrose with ...". I'm not familiar with US labelling law, but in the EU the first-listed ingredient is present at the highest level. And of course glucose is probably cheaper than aspartame so it would make commercial sense to use the highest amount of glucose possible while remaining "zero calories".

I don't have a definitive answer to this, but a little over a decade ago I was in an undergraduate lab that had a similar thing happen - a small amount of metabolism of a "control" group of bacteria fed artificial, sugar/calorie free sweeteners instead of sugar.
Our running theories at the time were:

Contamination. Always a problem in laboratory experiments, and especially undergraduate lab experiments.
Trace contaminants. "Zero calorie" isn't actually 0, it's just small, and hardy microorganisms may be able to do just fine with small amounts of nutrients. If there's another factor limiting their growth, that may result in the identical CO₂ results.
Some intermediate compound or the like that is useful for metabolism. As you said, possibly the ability to use maltodextrin or dextrose.


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Can cats use ketone bodies as only source of energy?
I recall reading that much of the energy a cat produces from its food comes from proteins which I assume would produce energy via being catabolised into amino acids which in turn, if glucogenic, would undergo gluconeogenesis and then, by means of being metabolised into glucose, enter glycolysis and the resulting pyruvate would be converted to acetyl-CoA and enter the TCA cycle to produce energy. I'm wondering whether this recollection is accurate and whether cats could, like humans, use ketone bodies for their sole fuel source if need be.

You are correct that cats consume a lot of protein, and it's safe to assume a large share of this is broken down to amino acids, which are then oxidized to produce energy. But amino acids in general are not catabolized via glucose; instead, they are converted into compounds that feed into the TCA cycle via other biochemical routes.
Almost every of the 20 proteinogenic amino acids have their own specialized catabolism pathway, so this is a large topic. The general theme is that the amine nitrogen is first removed by a transaminase to yield a keto-acid, which is when converted into a carbohydrate that can enter the TCA cycle. To give but one example, leucine is converted in the mitochondrion by a series of CoA-coupled intermediates into acetyl-CoA and acetoacetate (a ketone body; see below). The acetoacetate in turn yields two more acetyl-CoA. A description of this pathway is found at the HumanCyc database. This is a great resource for learning amino acid (and other) biochemical pathways, and provides literature references.
Some amino acids are indeed used for gluconeogenesis, mainly by the liver, but this is not a requirement for their catabolism by most tissues. (It would be energetically inefficient to first generate glucose and then break it down again!) An exception is the central nervous system, which does require glucose and cannot subsist on fat or amino acids (for reasons that, to my knowledge, are still not well understood). So in order to support the CNS on amino acids, the route your describe via gluconeogenesis does occur.
Ketone bodies (acetone, acetoacetate and beta-hydroxybutyrate) are the main alternatives to glucose accepted by the CNS. Gluconeogenesis is energetically expensive in the long run, and if deprived of dietary sugar for a long time, the body will increase its usage of ketone bodies instead of glucose. However, ketone bodies can never fully replace glucose: even during prolonged starvation in humans, blood glucose is kept > 2mM. The CNS would not function otherwise. I'm not an expert in cat physiology but I would bet the situation is similar.


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Which classes of drugs (filed by their pharmacology) induce a release of β-endorphin?
Which classes of drugs (filed by their binding sites) induce a release of β-endorphin? I know of agonists of the nAChRs and 5-HT1A and ethanol. Are there any others?
Please cite journal articles with links to the respective articles


text:
Why are there so many sex determining systems in animals
There are several sex determining systems in animals.
In mammals XY = male(except in rare cases where SRY crosses with genes on the X so that it is the reverse) and XX = female.
In  some birds it is just the opposite. That is XY(actually ZW) = fertile female and XX(actually ZZ) = fertile male.
In  some reptiles it is determined by temperature and has no genetic determination.
In lots of insects there is XX = female and X0 = male. This is usually accompanied by males being haploid and females being diploid like it is in bees.
In some insects and reptiles there is also the ZW/ZZ system but they are not dependent on it. In other words ZZW in some insects and reptiles can give rise to either sex but there is no temperature determination either.
Why are there so many sex determining systems? Why did animals evolve to not all have the familiar XY system? It must be so confusing as to which species has which sex determining system when biologists are trying to determine the gender of an animal.

Could not fit in a comment…
I don't quite know how to answer. I think that the only answer one could give is why not?. Various mechanisms may evolve under different life-history, different environment, different ecological strategy, different mutations occuring,..
In some species (including some amphibians) the evolution of sex determination system is highly dynamic and switch back and forth between one system and another.
I highly recommend the book: The Evolution of sex determination system (2014) that will give you a very good theoretical understanding of how sexual determination system evolve and make a complete review of empirical studies on the evolution and mechanisms of sex determination system. I think it is the only book existing on the subject.

I felt the same way ,thought of writing a comment but this will do.

Here's just the paper for you: Sex Determination: Why So Many Ways of Doing It? (Bachtrog et al, 2014.)
(And, it's open access!)
One important point is that although the initial "triggers" are diverse, the downstream pathways can be highly evolutionarily conserved.
Some tidbits from the paper:

ESD [Environmental Sex Determination] is favored over GSD [Genotypic Sex Determination] when specific environments are more beneficial to one sex, selecting for sex-determining mechanisms that match each sex to its best environment...
The reverse transition, from ESD to GSD, is thought to be favored when the environment is unpredictable or not variable enough, in which case ESD could produce strongly skewed sex ratios or intersex individuals.
In species with genotypic sex determination, the chromosome pair that determines sex can change rapidly over time... Sexually antagonistic selection, which occurs when a mutation is beneficial to one sex but detrimental to the other, can... drive transitions between sex determination by different pairs of chromosomes. For example, if an allele of an autosomal gene is beneficial to males but harmful to females and becomes linked to a dominant masculinizing mutation, then chromosomes that carry both the male-beneficial and male-dominant alleles create a novel Y that can replace the ancestral mechanisms. Conversely, alleles that benefit females and harm males can create novel W chromosomes when linked to feminizing mutations...

And more. Check it out!


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Blood type frequency given probability
I have calculated the probability that any child will have a particular blood type from both the genotype level and the phenotype level assuming the human ABO Rh system is followed.
Here are the genotype probabilities:
AA+/+ 49/1764
AA+/- 98/1764
AA-/- 49/1764
AO+/+ 98/1764
AO+/- 196/1764
AO-/- 98/1764
BB+/+ 49/1764
BB+/- 98/1764
BB-/- 49/1764
BO+/+ 98/1764
BO+/- 196/1764
BO-/- 98/1764
AB+/+ 98/1764
AB+/- 196/1764
AB-/- 98/1764
OO+/+ 49/1764
OO+/- 98/1764
OO-/- 49/1764

Here are the phenotype probabilities:
A+ 441/1764
A- 147/1764
B+ 441/1764
B- 147/1764
AB+ 294/1764
AB- 98/1764
O+ 147/1764
O- 49/1764

Here is the frequency of the blood types in the 1st generation by genotype:
AA+/+ 5/101
AA+/- 5/101
AA-/- 5/101
BB+/+ 5/101
BB+/- 5/101
BB-/- 5/101
AB+/+ 5/101
AB+/- 10/101
AB-/- 5/101
OO+/+ 5/101
OO+/- 5/101
OO-/- 5/101
AO+/- 10/101
AO+/+ 5/101
AO-/- 5/101
BO+/+ 4/101
BO+/- 4/101
BO-/- 4/101

Here are the numbers and their genders; a number represents an individual from a population of 101:

Male:
0,2,5,10,11,17,20,22,23,31,34,40,41,44,46,47,50,55,59,61,62,68,71,79,80,82,85,88,89,92,94,100

Hermaphroditic(and fertile):
4,8,16,25,32,64
all the rest are female
M/F mating: 11,904 offspring in 2nd generation H/A mating(hermaphrodites can mate with other hermaphrodites, males, females, and even themselves): 3636 offspring in 2nd generation
If you divide these by 6 you will get the amount per operation. The operations I am taking into consideration are +, -, *, /, ^, nth root, and arrow arrow(tetration).
So how can I take the frequency of blood types at the genotype level, probability of blood type at genotype and phenotype levels, and total number of offspring to get a 1st order estimate of the frequency of these blood types in the 2nd generation?

This question is very hard to read, I suggest that if you put some effort in to the formatting you'll more likely get a good answer :)

"Here are the numbers and their genders:" ... what do you mean here?

Since this biological data is from my Math World story numbers such as 0 and 100 have genders. Their gender is determined by 4 sex chromosomes. XXXX = female, XXXY = male, XXYY = hermaphroditic, and XYYY = male

So you mean there is 32(?) males, 6 hermaphrodites, and 101-(32+6) females??

yes that is what I mean

*"The operations I am taking into consideration are +, -, , /, ^, nth root, and arrow arrow(tetration).": This part is also unclear

In math world the eggs and sperm have these operational chromosomes. For arithmetic they are +, -, *, /, ^,nth root, and arrow arrow(tetration). Different combinations of egg and first sperm to fertilize it lead to different operations done with the numerical value of the mother and the father. The mother is always the first addend, first factor, dividend, minuend, base, index, or is an exponent and a base in the case of tetration(which is repeated exponentiation).


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In what ways can mechanisms of apoptosis be damaged?
How many ways can an Apoptosis mechanism be made disfunctional or irreparably damaged? If a cell has damaged Apoptosis mechanisms and it divides will its daughter cells have such damage?

Most of us have had the apoptotic process in our B-lymphocytes disrupted when we had infectious mononucleosis, caused by the EBV virus.  The EBV virus (pardon the virus-virus) encodes proteins, including one that mimics a host cell protein, Bcl-2, which plays an important role in apoptosis.  The set of virus 'decoy' proteins  forces the infected cell to survive and be a host to produce new virus, whereas the cell's normal response would be to apoptose.
Wart viruses such as HPV may have similar mechanisms.
So in summary, excessive growth or transformation to an immortal cell typically requires activation of mechanisms that promote cell growth and the inibition of mechanisms that promote cell death.  "Transforming viruses' often have mechanisms to affect both cell growth and cell death.
This answer isn't to the question 'how many ways can [the] apoptosis mechanism [..] be damaged ', but answers 'what's a common way that apoptosis pathways can be disrupted'.... large DNA transforming viruses.

Could a transfoming virus exist that could turn on apoptosis mechanisms? You could say all cells have self-destuction mechanisms(if I'm correct) , could a cancer cell with its excessive growth still have one type of 'self-destuction'mechanism 'left-over', or could daughter cancer cells have a self-destruct ability that is presently inactive?

@user128932. Could..possibly, although it would seem to be at odds with promoting growth.  Yes, there are at least 2 other cell death pathways that could act if apoptosis is disrupted, but they may share common pathways and may also be disrupted.  Will be cell type dependant.  Daughter cells would have the same phenotype as the parent cell if they: share the same mutations (see AndroidPenguin answer), share epigenetic modifications that alter apoptotic gene expression or the virus genome (and proteins) persists.

Do stem cells have apoptosis mechanisms? Could a stem cell having a 'self-destruction' mechanism repair the cell-death pathways in a cancer cell?

@user128932  I suggest you ask that as a separate question.

Lot's of ways. Apoptosis is complex, but falls under two pathways ending up at caspase 3. Anywhere in the pathway may there be a problem but also in things that trigger the pathway. For example in cancer there is loss of tumour suppressors which ensure a damaged cell undergoes apoptosis or prevents replication and oncogenes which allow controlled replication. Damage to these genes allows a cell to divide in the absence of signals to divide and also forget to check that it's DNA isn't damaged before replicating. This is then passed on to the daughter cancer cells. As each check is removed the cell permits more and more mutations meaning more and more likelihood for the next mutation to occur. Cancer is caused literally by one cell having defects and every daughter cell also possess the defects. Those that have defects which accidentally kill the cell are selected out.


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How long before robin no longer needs the nest on my porch?
A robin has made a nest on my porch. Unfortunately, the nest is on my weed wacker which I might want to use at some point this summer. Currently, there are two eggs in the nest.
How long will it be before the robin is done needing the nest?
Location is Eastern Massachusetts.
-- Update May 13 --
I think one of the eggs must have hatched. The robin no longer sits in the nest, she just stands on it constantly.

As cited in my answer, Cornell University Lab of Ornithology's All About Birds website is a trustworthy and excellent website for learning about any bird species across North America (and beyond?). The site contains many pictures and sound clips as well as tons of easy-to-read info about ecology and life histories.

Go to a crowdfunding site, state your concern for the robin's nest, get the cash to buy another weed wacker, everyone wins. Remember to send pics of the chicks to all the donors. If you associate crowdfunding with begging, tell them you are making a presale of robin chicks' photos. Even get some pro photographer from your region involved. Problem solved, nest saved. Donate any excess cash to WWF or any local wildlife preservation charity if you fancy. Post donation receipt online.

As a third option, there are professional bird catchers who can move the next without upsetting the mother too much. That would probably cost more than another weed-wacker though.

@Omegacron I expect the changes of succes to be low.

According to Cornell's All About Birds website, you will have to wait about a month for the nest to be cleared.

The egg incubation period is 12–14 days.
Following hatching, the nestlings will remain in the nest for another 13 days (i.e., the "nestling period" is 13 days).

However, there are two caveats to this:

A typical robin clutch size (i.e. the # of eggs in the nest at once) is 3-5 eggs. Since you only have two eggs, that could suggest that more eggs are about to be laid very soon, which may extend the nest occupancy another day or so.
Some robins use the nest more than once!

An American Robin can produce three successful broods in one year.

Here's a visual of what the nestling period (approximately) looks like so that you can track your nest visually :) :

 Source: L. Birnbaum


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How to correctly and accurately identify a few species of trees from their leaves?
I want to identify a tree from one of the 12 species listed based on observing their branch and leaves. Is there quick and neat way to do it?
Red Oak, White Oak, Red Maple, Striped Maple, Tulip Poplar, Black Cherry, White Pine, Virginia Pine, Dogwood, Hickory Species, Sourwood and Cucumber Magnolia.
Thank you!

Yes. Get examples of each tree (or Google), then memorize their structure and features. It's quite easy...

Becoming familiar with the leaves and bark of various trees really is the best way of identifying them, even if you just know it's an oak tree, for example, but not what kind, as all oaks have the same basic leaf structure. Learning to identify the subtypes just takes a little more work.

@MattDMo I understand, but that should be so obvious of a method as to not warrant a question, at least not in a day and age of Google. Say I was going on a trip to the American Southwest and I wanted to be able to identify the different types of Cacti, I'd do a few Google searches. I think we need to start a stack for questions on how to do basic queries. There is only one thing that I can think of that would warrant that, and it is if the OP is in a country that censors sites such as Google, etc. What we take for granted in Western countries cannot be taken for granted elsewhere.

@AMR let's discuss this more in chat - it's not really pertinent to this question.

This online key (and app) can probably help you: Arbor Day Foundation: What Tree Is That?

@MattDMo actually oaks have wildly different leaf structures.  See *Q. phellos, Q. nigra, and Q. Michauxii as examples. However many oak species found in the Appalachians and surrounding  southeastern and mid Atlantic piedmont (where the OP is certainly located) do typically have a fairly standard 'shape'  (though not to a novice)

A good first step is to pay attention to common differences between tree structure:

Alternate vs. Opposite structure

MADHORSE = your common eastern US opposite-leaved trees are Maple, Ash, Dogwood, and Horsechestnut (AKA buckeye).

Simple vs. compound leaves

Toothed ("entire") vs. untoothed leaves

Lobed vs. unlobed leaves

Differences in texture, hairiness, & color of leaves

both b/w species and b/w top/bottom of leaves of the same species

Generally when you come across a new tree in Eastern N. America I'd recommend going through these steps:

Is it alternate or opposite?
Is it simple or compound?
Is it toothed, doubly-toothed, or smooth along the edge?

If you can answer yes to (any or all of) those questions you typically SIGNIFICANTLY reduce your options.
You also want to make sure you're aware of large variations in some species (especially oaks and hickories). One good example is the difference in shape, texture, and color of sun leaves vs. shade leaves of many species.
Importantly, paying attention to WHERE the tree is located (and what else is growing around it) as this can really help narrow your choices. You'll also start recognizing common cohabitants of certain habitats.
Finally, don't be afraid to use your many senses (smelling, feeling and even tasting) -- though get to know poison ivy well before you start licking plants!!

Ok, now for some useful hints:

Red Oak = stereotypical oak shape (i.e., pinnately lobed), smooth on both side of leaf, lobes are not deep. You'll find 'spikes' at the end of each lobe. Bark looks like it has vertical shiny stripes.

White Oak = rounded SMOOTH lobes. Bark light grey/white with flaking appearance when mature

Red Maple = OPPOSITE. Leaves serrated (toothed). Smooth grey bark (with few low-hanging branches)

Sugar Maple = OPPOSITE. Leaves NOT serrated. Smooth whiter grey bark.

Striped Maple = OPPOSITE. Maple-like shape, but with rounded/butt-shaped (cordate) base. Bark = very striped in appearance.

Tulip Poplar = Leaf-shape looks like a tulip flower. Tree tall and straight.

Black Cherry = Oval/round leaves with fine single-toothing along edge. Tuft of brown/white fur along mid-rib on underside of leaf. Bark = horizontal striping due to lenticels; gets flaky when mature. Bark/twigs have strong bad smell when scratched (cyanide).

White Pine = 5 relatively long wispy needles per cluster.

Virginia Pine = 3 Short, dense needles per cluster.  Bark has cornflake appearance.

Dogwood = OPPOSITE. round leaf with deep ribbing veins and drip tip. Leaves often look to be growing in pairs. If you pull a leaf apart carefully, you'll find some thin tissues dangling between the halves. The bark is cobblestone (mosaic bumpy) and the shape of the tree is typically flat-umbrella-esque.

Hickory Species = VERY DIFFICULT TO TELL SPECIES APART (though I can give you a bunch of hints to help). Fairly easy to tell apart from other species, though. Is ALTERNATE + COMPOUND with generally 5-9 leaflets per leaf. (unlike ash = opposite/compound or walnut = compound with MANY leaflets). Leaves often carry some odor and large seeds can be found nearby

Sourwood = Long, oval, tiny-toothed leaves that have strong sunken midrib and thin leaf texture. Tastes very sour. Bark is dark and ridged, and trunks very rarely grow straight (so look for crooked or leaning trees!).

Cucumber Magnolia = Look for LARGE, strongly veined leaves that are often drooping. Look for circular ring (stipule scar) beneath leaf petiole base.

Old post, but this is a ridiculous resource.


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How are subspecies defined, in contrast to species?
When should a taxon be considered to be a subspecies of a certain species, and when as a different species? Are there some general guidelines how to assign a specific taxonomic status to a taxon?

This Q is more similar to What is a subspecies?, and should be closed as a duplicate to that question.

Also see the questions http://biology.stackexchange.com/questions/26105/what-is-difference-between-breed-variant-subspecies-and-species and http://biology.stackexchange.com/q/14414/3624


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Have scientists ever produce a new species in laboratory by means of natural selection?
I was wondering, if scientists ever produce a more complex species from a less complex species by means of natural selection? I imagine something like, bacteria which can't photosynthesis and oxygen (chemoautotrophs) to bacteria that can photosynthesis and oxygen like cyanobacteria.
If scientists have never done this, is this theoretically possible to be done in lab by means of natural selection?

If you have plenty of time and all the needed enviromental interactions, then, it should be theoretically possible.

There was a case I remember that involved genetic drift and not natural selection: https://en.wikipedia.org/wiki/E._coli_long-term_evolution_experiment

The term species is poorly defined concept (see here) and as a consequence the question is unclear. However, using the standard concept of species based on reproductive isolation, then the question has been asked (for Drosophila) here and your question is therefore a duplicate.

The question also suggests that you have a few misunderstanding about evolutionary biology. You might want to get some introductory knowledge in this field. Understanding Evolution (UC Berkeley) is a good (and free) online source of information.

@Remi.b I don't get your recent comments about species as a poorly defined concept. By the same logic you are applying here, all questions dealing with or mentioning species should be closed as unclear, which is hardly constructive. Irrespectively of your scepticism towards it, 'species' is fundamental concept in biology, and people should be able to ask about it here at Bio-SE without having to jump through hoops.

If I understand you correctly, the changes you are considering are huge evolutionary steps and not the type of changes you would normally see during speciation. You should also consider that species concepts in bacteria are usually quite different than those used in other taxonomic groups.

@fileunderwater There are ties when the exact definition matter little and times when it is important. You commented yourself on the species concept and what "kind of evolutionary change" is the OP looking for. This is here all I meant. Once the OP understands the concept of species, (s)he will understand why his/her question makes little sense. Note also, that I voted to close as duplicate and not as unclear.

Some people will argue HeLa cells fit this bill, but that's a subject of debate.

There are a few issues your question brings up.  First, the idea that species evolve from simple to complex is actually not a prediction or inevitable consequence of evolution by natural selection.  The terms "simple" and "complex" themselves are ill-defined.  For instance, if you defined "complex" to be size of the genome, the most complex organism found to date is probably a flowering plant from Japan.  This idea of arranging organisms from simple to complex hearkens back to a pre-Darwinian idea of the Great Chain of Being.
You may be thinking that since multicellular life, for example, evolved from single-celled organisms, mutlticellular life is more complex than single celled life.  The fallacy is that modern single celled organisms also evolved from the same single-celled ancestor.  In no evolutionary sense is modern multicellular life more evolved than modern single celled organisms. You can, of course, defined notions of complexity to make multicellular life more complex than single celled life, but such definitions have no evolutionary significance.
We can, of course, say that organisms evolved from earlier organisms.  So the second issue your question brings up is have scientists seen large evolutionary changes in a laboratory setting.  The example you bring up is whether we could observe the evolution of photosynthesis in a lab.
The short answer is no.  We would not expect traits which took millions of years to evolve to evolve in a lab in a shorter amount of time.  In the case of photosynthesis, we may not even have a good idea what selective pressures were involved early in the evolution of cyanobacteria.  Such traits do not usually evolve in their totality in one step.  Instead there are many steps along the way, each of which may be selected for in particular environments for different reasons.  Even if we had millions of years and a very large lab, we may not know of these early selective pressures to successfully recreate the evolution of a particular trait. (There's actually a bit more depth here which I am glossing over. Since the variation in the population is different, the same series of selective pressures won't necessarily yield the same outcome.  When traits evolve through convergent evolution, which is what you are suggesting, they virtually always have different genetic bases and underlying biochemistry.  But a digression into this is probably a distraction from the central point.)
So, you may reasonably ask, if we can not directly observe the evolution of these major traits in a lab, how do we know that they evolved?  There are multiple lines of evidence:

We can see smaller changes occur in shorter periods of time, so it seems likely that the same process creates larger changes in longer periods of time.
For many large traits, we see evidence of common ancestry and the same underlying biology being used for different purposes.
For some traits, we have the evolutionary history of that trait and can identify the sequence of events which brought that trait about (the best evidence generally comes from skeletal traits, where there's preservation).
More speculative evolutionary histories can still be examined through genetic techniques such as molecular clocks, which can indicate when species diverged from a common ancestor.

By most definitions Rick Lenski's Long Term Evolution Experiment has produced a new species in the lab.


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Is it possible for a child to grow taller than their tallest parent?
I have heard that offspring can't grow taller than either of their parents but I've also heard that sometimes some gene activation can skip generations. Is it possible for a child to grow taller than their tallest parent?

Where did you heard that? Have you read it somewhere?

there are several examples of offsprings taller than their parents.

well, if that was true, primitive humans would have been a lot taller than us. And, eventually, humans would become hobbits, as far as height goes =P

Well.. I am taller than both of my parents. Phenotypic variance is the addition of the enviornmental variance and the genetic variance (and their covariance). In other words, the environment, not only the genes influence someone's height. This is one reason that may explain why an offsrping may be taller that their parents.

An easily visualized example of where even completely genetic traits don't simply average parent phenotypes is hair color: many dark haired parents have bright blond children when each parent has a recessive blond gene.

because people grow taller over generations this has to be true doesn't it :)

If it were true, wouldn't it likewise be true that no child could be shorter than their shorter parent?  Which would mean that eventually all humans would be the same height?

People can grow taller than their parents. Anecdotally: I'm 185 cm, my parents are 155 cm and 178 cm. Joakim Noah, an NBA basketball player is 211 cm, his dad was 193 cm and mother was 175 cm... how?
Genetics and environment play a role in determining height. First of all, a more nutritious environment during development can lead to increased height, this is one reason why more recent generations appear to be taller.
Height is also an example of a quantitative trait - this means many genes (or loci [singular is locus], locations in the DNA) affect the phenotype (the physical measurable result i.e. a persons height). It is infact how the vast majority of traits are determined. At each locus that affects height there may be polymorphism (when more than one allele, or variant of that gene, exists).
Example:
Suppose height entirely is determined by 2 additive loci, $A$ and $B$, and no environmental effect occurs, and there is diploidy (two of each locus, one from each parent, determines height in a person).
Each locus has two alleles denoted by $A_1$, $A_2$, $B_1 $ and $B_2$. Each copy of alleles $A_1$ and $B_1$ add 40 cm to a persons height, $A_2$ and $B_2$ add 50 cm to a persons height.
Now a man who is $A_1 A_1, B_1 B_2$ (remember, humans are diploid) and a woman who is $A_2 A_1, B_1 B_1$ have children. Both parents are 170 cm tall. The theoretical limits for the population would be 160 cm and 200 cm. The children will inherit one copy of $A_1$ from the father and $B_1$ from the mother, but they could inherit either $B_1$ or $B_2$ from the father and either $A_1$ or $A_2$ from the mother. If a child inherited both of the taller alleles then they would be taller than the parents ($A_1 A_2, B_1 B_2$ = 180 cm). Likewise some offspring could be shorter.
Of course the reality is much more complex; height is determined by many more than 2 loci, by the environment, and gene * environment interactions. This principle was a hugely important because it meant that reproduction did not necessarily remove variation from the gene pool (a fundamental problem with early evolutionary theory was the thought of "blending" - when offspring are the average of their parents)

Yes, people can definitely grow taller than their parents. Height is a polygenic quantitative trait (so affected by many genes), that is also strongly affected by environmental factors. You are also forgetting that there is a sex difference in height (~14 cm, Wright & Cheetham, 1999), so the height of the mother does for instance not set an absolute cap on the height of her sons ("....can't grow taller than either of their parents"), but her genetic background will influence their heights. If both parents are e.g. 180 cm tall, that is close to the population average for the father but considered tall for the mother, she is likely to carry genes that contribute to her offspring being tall.
That height is a polygenetic quantitative trait means that parental height will be a good predictor of offspring height, but with a wide scatter around the mean. Normally, 90% of children fall within 1.5 standard deviations of their midparental heights, after being sex-adjusted with +- 7cm for boys and girls (Wright & Cheetham, 1999). For simplicity, it is often said that 90% of children will fall within 10cm of the sex-adjusted mid-parental height. However, the deviations are smaller if the parents are unusually short or tall, representing "regression to the mean", and parental height is a poorer predictor for offspring height in these cases. Using the midparent mean as a predictor of offspring height is otherwise standard practice, as can be seen in online applications (e.g. http://medcalc3000.com/HeightPotential.htm). Using the same example as above, with both parents being 180 cm, will predict an offspring height of 186cm for sons and 174cm for daughters.
That height is strongly influenced by nutrition has been clearly shown in the general secular trend in body height in developed countries over the last centuries (Cole, 2003, where the average height of successive generations have been taller than their parents. For instance, the average height in the Netherlands have increased from 165 cm in 1860 to 181 cm in 1990 (numbers from Cole, 2003). Some of the online height calculators you see will also include a corrections for this, and add e.g. 1-2 cm to the mid-parent heights before correcting for sex.

Yes it is quite possible, recall nature vs nurture. I myself am slightly taller than both of my parents by about a head. As long as you have sufficient nutrition it should be quite possible.
And what you said about gene activation skipping generations is quite true- it can indeed happen, and if the gene responsible for height is not expressed in the parents but is in their offspring then it will also be more likely for the child to grow taller than their parent.