CharonY

If it was, it is quite a mess of questions. It kind of garbles up a number of terms, IMO.

Not like that. There are too many uncertainties (i.e. environmental factors) that would be impossible to predict population-wide changes. The only possibility would be under highly controlled conditions (the Lenski experiment would be an example). I was given the example of function prediction based on the protein sequence. I think the basics should be covered in quite some textbooks. Check this out, for example http://www.ncbi.nlm.nih.gov/books/NBK21086/. Without evolution as a basis the whole approach would be non-sensical.

Of course biology has models or predictive power. In many cases they tend to be more qualitative in nature, however. You may want to look up how e.g. genome annotations are conducted, just to get an idea on this topic.

I think we are in different incompatibility groups.

I feel you may still be missing the point. Let us say, we want to sequence an organism. First of all, we would assume that DNA is the carrier of genetic information. Why? Because evolution. Then, if we sequence it, we use methods that differentiate the four bases. Why? Because evolution. The way we then detect open reading frames, deduce protein coding sequences, identify the amino acid sequence thereof and predict functions are all possible under the theoretical framework of evolutionary theories. Without them the approach would have to be radically different. It is therefore not only selector of bullshit (which it sometimes is, but probably not that often in a scientific context) but it is really the foundation of many actual approaches.

The point is that while you are still learning the basics, it is very unlikely that you will come up with any relevant or novel ideas. As others have said, you have to know the current knowledge on a given subject (which takes quite a while to master) and then you can develop new ones. Many ideas that you will have now, will appear foolish to you, once you have studied them further. One of the first prerequisites of learning is humility. One has to acknowledge that the knowledge one currently has is insufficient. Only then does one open ones mind to learning. Incidentally, much of the college time will be spent realizing how little we know in various fields. Much what we have learned from textbooks in high school are just extreme simplifications to make the topics more digestible. The desire to try to understand even a tiny little bit more is what drives scientists. But first one has to have a (somewhat) clear vision what is known and what not.

It is actually slightly more complicated. Bottom line is (as correctly pointed out) cold restricts blood flow, numbs pain and reduces inflammation. Heat promotes flow. The question is therefore less whether the pain is acute or chronic, but rather what the mechanism behind it is. For most acute injuries pain numbing and reduction of inflammation is beneficial. However, even with chronic pain cold can be advantageous if the source is inflammation. However, heat can promote injury healing (by increasing blood flow)...

Ann interesting article describing how young gorillas learned to spot and dismantle traps. http://news.nationalgeographic.com/news/2012/07/120719-young-gorillas-juvenile-traps-snares-rwanda-science-fossey/?source=hp_dl2_news_smart_gorillas20120720

This is not my field, but do you have an specific questions in mind?

I am quite confused. In the provided link the author (Dean Baker) is actually saying that Krauthammer is just giving "the right-wing caricature of the left". And then continues stating that I wonder whether you agree with Krauthammer or Baker here. Krauthammer's post is mostly a drivel attacking Obama using repetitions of well-known talking points starting with misquoting Obama. "Caricature" is actually quite fitting. So, a lot of opinion there, but little theory.

If you are lazy and have access, solid phase extraction columns with C18 can also be used. Or pack them yourself (though arguably doing LLE is easier at that point).

Bloody hell. And pretty good posts on top of that. Also it made me realize how many fans he got. Why are physicists always the popular ones? And how does he keep up with his work? I have to steal his delicious brain. Hmm, brains.

This is rather an oversimplification and a comparison that does not hold much water. First of all a virus is generally considered a mobile genetic element rather than an organism. Second of all, infections have in common that they need to find a compatible host, circumvent immune responses and possibly deal with competition in their particular niche. Now here is the point were strong or weak is something that is not really useful in the discussion of diseases. First of all, quite a few of the symptoms involved in disease response, including some rather harmful ones, are not due to the primary actions of the pathogen, but are triggered by the immune system. The cytokine storm is the textbook example for this. In this case a strong immune system (in terms of giving strong immunoanswers) becomes a liability. Second, most pathogens do not actively try to hunt down their prey. In fact letting them survive is quite an efficient tactic, too (just look at all the viral DNA in our genome). Especially in viruses a longer co-evolution between host and pathogen results in lower virulence.

This is not even a question...?

Well, if it is accurate I wouldn't call it unprofessional....

Actually, I think that the idea of having to take up loans or receiving scholarships just to get a higher education is a bad one. A certain level of education (and ideally the associated broadening of one's perspective) is something that benefits society as a whole and levels the playing field. Whether colleges are well designed to achieve that may be a slightly different issue, though.

What do you mean with saturated by study? Too many people working on it?

Well, a 1600 lumens LED is apparently being released commercially My link. The efficacy is 80 lm/W.

Just wanted to respond to a point in the OP, evolutionary theories are often less applicable to unicellular organisms as several mechanisms, including horizontal gene transfer but also problems in defining species make it actually harder than for other organisms. That being said, Arete essentially responded to it perfectly, it is the all-encompassing theoretical framework that holds biology together. One may have to dig a bit to appreciate how relevant it really is, but it is necessary as a foundation for almost all areas, from molecular biology (thinking in terms of structure-function relationships, sequence similarities etc), to ecological networks.

Remind me, the insert was cut out from an existing vector? If so you can also try to ligate without further treatment. I do not understand the last sentence. Does the insert encode amp resistance, or the vector from which it is derived?

If you used the nanodrop you should get a concentration. Thus you know how many ng you got per ml, for instance. Based on that you can e.g. start with one microliter of insert and calculated how much you need to have 1:3 molar ratio (generally low volumes are used so that dilutions with the ligation buffer are easier). For the next questions in order: - You should see few colonies if the digest worked. There are almost always a few plasmids that do not get restricted (you won't see them on the gel, usually). This is just to control for restriction and to be able to calculate the ligation efficiency. - Yes, this is just to test that your vector is properly transformed with your protocol. - This is to test whether you got some issues with the extraction from gel. And if you compare the amount of colonies from a simply re-ligated vector to the digest (if you transform with similar concentrations) you can see whether your ligation was efficient. If e.g. the number of colonies is the same as the digested vector, it would indicate that the ligation did not work. If everything works except your approach after agarose purification it may indicate an error at that step.

I think I phrased it incorrectly and slightly confusing. However, the ratio that I meant is not the PPV (the sentence would not make sense if it was), but the ratio between true associations and no associations, or in the standard notation TP/TN. Just to make it clearer [latex]PPV=\frac{(1-\beta )\times R}{((1-\beta)\times R)+ \alpha } [/latex] With R being the ratio of true associations to the rest (no association), a value that is generally unknown. Regarding corrections such as Bonferroni or the mentioned Dunn-Sidak, these more stringent approaches have the disadvantage that they increase tthe false negatives. And in the case of Dunn-Sidak, the hypotheses have to be independent (which is not easily determined in epi-studies). But note that we only adjust our threshold to maintain the error level (say, 5%). As you can see that the PPV will still depend on largely on R relative to alpha (which was my main point). Validation studies are always needed and as it turns out, even with proper multiple-hypothesis correction, the issue of FP is not resolved, when the search space expands (a common problem in omics and epi-studies).

Essentially you calculate how much vector and insert you have (based on conc measurement and adjustment by bp). I.e. you just multiply the ng of whatever DNA you have with the bp length. It is not absolutely precise, but often close enough. Usually a slightly higher amount of insert is used (around 3:1). Though in the end it is quite a bit trial and error. Precisely. If you do tha you can figure out how efficient your ligation is (by transforming the digest and by transforming the ligated plasmid and comparing the number of transformants). But as the first step I would now suggest checking whether your cells are still competent (i.e. transforming your isolated plasmid).

Stat only will not correct for that. A critical point is the number of correlations tested vs the number of true associations. Multiple hypothesis corrections do work, but still deliver false positives. A critical relationship is the type I error in relationship to the ratio of the number of true associations relative to false associations, in other words, the positive predictive value. If we assume that for a given data set only 5% of all tested relationships are true (which is a lot) and were tested to be statistically significant with an corrected alpha of 5%, then the chance of for a statistically significant hit to be true (i.e. the PPV) is 50%.

This is tricky as high-dimensional data tends to exhibit patterns that appear to be statistically significant yet in truth are not related. Stronger support are studies from different angles that support the hypothesis (and none or only few that contradict it). To my knowledge and a brief scan through recent articles indicate that the hygiene hypothesis holds up well (i.e. the postulated inverse relationship was found more than a few times). Also, a recent paper showed that reduced exposure to germs resulted in an expansion of natural T killer cells, which are involved in colitis and asthma. (forgot the reference but should be from Blumberg and Kaspar). While the latter was done in mouse models, it provides a mechanistic explanation.