CharonY

Some journals also actively ask existing reviewers whether they can recommend someone. It is kind of a community service.

Both are useful (i.e. petpide mass fingerprinting and full sized MS). The first is more convenient, however there is always the possibility that somehow your recombinant product got something that it should not have. You would have to check all acquired spectra, although unidentified peaks could also have other sources). Full sized MS (e.g. with a MALDI) can give you at least the average mass of the thing. You would have to use the right matrix, of course.

Actually it is archaea and bacteria (eubacteria has been ditched as a term). The question is actually kind of invalid as the three domains of life classification according to Woese does not include protists (ditched as a taxon) or protozoa. Protists existed in the five kingdom system according to Whittaker consisting of animalia, planta, fungi, protista and monera. Again, it is not really used anymore.

No caffeine and candy? The end of science.

Isn't the OP essentially describing a Hardy-Weinberg situation, only with selective forces that move towards rather than away from equilibrium?

OK, based on that the only question is whether your old proteins still run as they are supposed to. If they do then it is obviously a property of your proteins. IIRC helicases had a different electrophoretic mobility as compared to their size, but I haven't got any calculations at hand. Deviations of up to 5kD from any given markers are, as a whole, not that unusual, though. The important bit is to establish the identity of the protein in question. If you have access to an MS I would try that instead of trying to tweak the condition to have it match the size.

a) what markers do you use b) are they prelabeled? c) are the proteins in question membrane proteins?

Too hot water will increase the amount some of the bitter compounds that you will normally get in your coffee. The effect is that the coffee will taste like crap but it is nothing new that you get into your coffee.

There are statistics out there that split up the proportion of religiosity among scientists from different countries. I will have to see whether I can dig them up again. But off the top of my head the tendency were that a smaller proportion of scientists are religious compared to the average of the population. Among scientists the natural scientist were the least religious. And among those the order was roughly physicists, chemists and biologists in descending order of religiosity. One exceptions was one poll in which biologists and medical sciences were put together . There the biologists + MDs ranked together with chemists, I think (i.e. medical scientists tend to be more religious than biologists). In many areas faith and the actual work does not interfere and hence is not seen as a contradiction. People are very good in compartmentalizing thoughts. Still, I presume that evolutionary biologists still tend to be the most godless bunch of them all.

This is one of the joys of epidemiological research. In the absence of mechnisms they basically find correlations but not causation (despite the fact that some claim they do). The majority of the research I am aware of found no link. In order to evaluate that in more detail one would have to look at the papers in very close detail, at least in order to see e.g. the methodological differences between the study, the composition of the study population, etc. It is important to keep in mind that the goal of epi-studies is not to provide causation but to provide possible links that can then be investigated in detail.

Or more fuel efficient cars in Europe because gasoline is so darn expensive there.

Uh. Litres? No idea. But as they are more stable in dried form I would search for that instead. Sigma for instance sells 500 g of rhodamine for around 130 bucks, fluorescein was around 200, I think.

This cannot be easily answered. You first would have to know the precise toxicity mechanism of theobromine and whether it is applicable at all to hydras, which have a vastly different metabolism as mammals, for instance. Even if you know how it affects hydras predicting dose-response relationships is not an easy task either (just take into account parameters like bioavailabilty, rate of metabolization, bioaccumulation etc). The easiest thing is probably just test it empirically. The solubility is much easier to figure out. According to some random MSDS sheets it appears to have a solubility of around 0.5g/l.

That kit should give a higher yield (in the µg range). It sounds like there is an upstream problem. What cells are those and how much do you use per extraction? One common problem is the efficiency of lysis, for example. Or you just do not have enough starting material.

Actually I am curious as well. While I have quite a few colleagues and friends in biological and chemical sciences who made successful transitions into industry, the majority of people I worked with in the area of physics and mathematics have stuck to academia. The only exceptions were a few experimental physicists who essentially continued working with the systems with which they worked during their PhD. I.e. they are now mostly application specialists or selling the instruments in question. I am thinking in the area of applied statistics, for instance. I assume that few actually require a PhD (but I may be wrong).

In order to give suggestions for increasing yield per isolation I would have to know from which substrate you isolate RNA as well as the precise technique. Pooling does not result in loss per se, though intermediate handling (e.g. freeze/thawing, contamination with RNAse, etc.) can degrade your sample over time. Also, depending on your downstream application concentration may be an issue. In that case one can use one of the concentration columns or precipitation techniques. In this case a bit loss is usually to be expected.

The "official" impact factor can be seen on the Journal citation reports by Thomson. You need institutional access to see them, though.

Well, it is not that surprising then. As it has been pointed out the expected IF depends highly on the field. An impact of around 2 appears not too high to me (i.e. an expected average of two citations per year). But then it depends on the pure amount of papers published to what actually gets cited (i.e. crap to gold ratio). A very small field can relatively high impact, if all the papers get cited. I recall that the highest for microbiological papers was around 4-5. Here papers in journals with impacts of lower 1.5-2 tend to be thought of as "crap" papers. Where I am currently working on (closer to the biomedical area) the breadth is even higher. The top includes journals like Cell, whereas the bottom can scratch around 1. So depending on the field the standards as what is believed to be acceptable varies (unsurprisingly) a lot. Also there is of course a difference in the evaluation between experimental and theoretical works even within a discipline. I do find it surprising if one low IF factor should have such an impact on hiring, unless of course there were either other reasons or it was the only distinguishing factor from other candidates.

Uhm, isn't its IF around 2? Or am I confusing it with something else?

Mononucleosis is caused by the infection with the Epstein-Barr virus. In the later phases it infects B-Cells. The infected B-cells in turn activate immune responses against them.

There is little reason to use GFP in Southerns. But there are uses for GFP antibodies. Search for that term, maybe in conjunction with Western and you should find something.

A postdoc is a transient position between PhD and whatever comes afterwards (usually some kind of professor in academia or company position in the real world). It is a bit of a limbo between having a degree and finally making a career. In other words one does not only become an ex-postdoc eventually (depending on country and system this may take anywhere from 6 months to several years), but one really wants to leave that part behind and work on a career instead.

1) as Mokele said. However, usually the corresponding author is making that request (in case it is not you). In addition, you may want to look at the journal policies. Some state their average review time and you may want to ask earlier in some cases. Depending on field and journal sometimes after three months a request can be reasonable. 2) You can always retract it, but if you submit somewhere else the process starts anew. You should not submit while it is still in review (for reasons already stated). In general it is customary to wait for the response of the review first and then decide to resubmit it or look for a different journal (depending on whether it accepted and the amount of changes/additional experiments required for publication). Fairness was never part of the equation. If you think this is bad then try to survive on grant money. But on average one tends to get the decision after 3 months (again, depending on journal). Personally, I had decisions as fast as one month and as long as four. Edit: Normally not. Also, reviewers are usually anonymous. Unless you become regular reviewer of a journal (as opposed as getting forced to write for an advisor). Then some write it on their CV (I do not, though).

That is a pretty good description, although many journals now have a sophisticated submission system (instead of email) that tries to prevents you from uploading relevant figures and tables or garbles up your main text (I assume that it tries to convert every third word into Chinese during the process). So that in the end you will have to give up and mail it anyway. Only to be referred back to the system. In addition, 15 has to be amended with: (you NEED to check every line for errors that they may have built in...) As already noted, most papers only accept papers that are not submitted elsewhere. In addition, you may end up with the same reviewer that will get pissed because they got the same article for reviewing twice. For many journals this is sufficient reason to reject the publication. Edited to add: It also depends on the field. Most natural sciences follow a similar scheme, but there are slightly different flavors.

In a number of disciplines there is virtually not glass ceiling beyond the master's degree. It depends on the company, of course, and what paths they offer. It would be worthwhile to research it for companies you might be interested in working for. I recall that the chemical industry still prefers PhDs but more computational dependent areas are also happy to offer paths for master's, for instance. You have to realize that a business degree itself is barely a job by itself, nor (similar to PhD) does it offer a job, unless you know the path you want to walk. Then you should check what you need to get there. At this moment it appears to me that you do the reverse.