CharonY

I think I have an account there, too. But as I did not find anything interesting in the biology section either, I decided not to stay there. Here at least I can enjoy Mokele's posts.

The hard part is that biology PhDs have strong competition from a lot of other disciplines (e.g. biochemistry, chemistry, pharmacology, medical sciences, bioengineering etc.), when it comes to jobs. In many cases the competition is better suited to industry needs, too. Biology is a bit too much of a jack-of-all-trades. The thing you have to keep in mind is that you do not need to find a position doing precisely what you did. Companies expect you to learn as you go along. To leverage from your education as much as possible you can look for sequencing and sequencing related companies and next-gen is still hyped right now (though it is becoming more mainstream by the minute). Remember, however, that you are not bound to do precisely what you studied. Just use your education as the primer as most companies expect you to learn on-job anyway. Many biology students (and also PhDs) do not apply to certain jobs as they feel that they do not fulfill all criteria, but especially on the masters level a certain switch (e.g. towards a more IT related field) can be explainable. Just make sure to justify it properly and emphasize any strengths (e.g. programming abilities) that you may have gained. I have an inkling what the future of biology will be, but I think it will be a lengthy essay. Also it of course depends on whether we are talking about biology in academia or in real jobs. In the latter biology always had problems, due to what I mentioned above (as well as a number of other issues).

Ugh, can we move that out of the evolution section? It makes my eyes bleed.

I have no precise figures at hand, but the rejection rate in the top-tier journals like Science and Nature tend to be around 80%. Most actually without being peer-reviewed, but directly rejected (out of scope or insufficient impact). I do not know how many of those actually sent to review are still getting rejected. I assume the rate to be much higher, too (based on what I am hearing).

I would put emphasize on the IT elements of your studies, and try that angle. There are companies in the biotech area (especially sequencing related) that hire bioinformatic masters for data analysis or software development. Especially the latter is still a somewhat good market. If you know that you do not want to go the PhD route, then do not. Mathematics is not really an important factor in business, per se.

This is something that you probably won't find out, as there is afaik no database that keeps track of non-accepted submissions. I would assume it would be kept confidential between the author and the editor (as well as reviewers). Your best bet is to look at journals that have specialized in evolution papers and see if they post their acceptance ratios. I kind of doubt it, though.

And again, this was an approach adopted after sequence databases were common. Before that it was quite a challenge to find the the position of a gene (in minutes of conjugation, for instance), not mentioning the trouble in the identification of the actual promoter...

apricimo, the information came from various sides, not just from one point. Without the use of DNA sequence traditionally proteins were sequenced with Edman. So even without a database to begin with, you could decipher the sequence of a protein, and give it a name. Large scale sequencing projects have changed that somewhat. The scenario described above does not make sense in the absence of sequence data as the question would be, how did you isolate that particular mRNA to begin with? And why? What is the hypothesis? What you describe is more a less a blind screening procedure and these require databases. Realistically, however there are other, more likely scenarios in the absence of sequence data. The most common one is reverse genetics. It goes like this: you want to identify e.g. the gene for a given function. You make e.g. a transposon mutagenesis and screen for cells that lose this function, due to disruption with that transposon. As the transposon has a known sequence, you can proceed to identify the DNA region in which it jumped into (e.g. by direct sequencing or Southern). Once you got the region, you can sequence it, based on the sequence you can deduce the protein sequence and as you already know its function (due to the method of identifying it) you can give it a nice name and put it in a database for everyone to see.

I have used the biodocit a while back. While not stellar, it certainly is sufficient for standard use. You should take care that the system you get is large enough for your gels. At that time i used mini-gels, so it was not an issue, but I think some of the oversized ones would makes some problems.

Generally, most people are unhappy to have EtBr on their fluorescence scanners. But with regards to simple EtBr gel scanners the prices tend to start around 5k (e.g. from UVP). Generally they save the thing in standard picture formats, have densitometry tools integrated (which I almost never used). Most are network enabled or you can use SD-cards to transfer data. Alternatively you can put the things together yourself. It takes a little bit more time though. The only crucial bit is a good CCD camera, but I have seen stations with rather cheap ones working fairly well. The overall cost may be around 1-2k. But if you do not want to deal with that maybe get the station and ask for rebates.

You are not giving a crucial point of info: what stains do you intend to use. EtBr, of course is easy as you just need a decent UV source. But for Western, for instance you have got a wide range of fluorophores and/or enzymatic detection methods that it is not quite possible to give any recommendations, if you do not provide specific excitation/emission ranges. A Typhoon system, could do about everything, for instance, but it would be way over the proposed budget.

Most research point out that the effects on health of stevia is less pronounced than e.g. use of fructose sweeteners.

The question is how you define it and based on what premises. Edit: Mooeypoo was faster and more eloquent.

Unfortunately I cannot see the spectra in the pictures properly. During interpretation of MS data you have to be careful to remember that the compounds are not necessarily single-charged (depending on compound and ionization method) and that they may fragment (again, dependent on ionization method).

So what do you think do these spectra tell you?

It is a bit unfortunate that you have not diluted it more to obtain colonies. However, if they form streaks it is extremely unusual to see only black dots instead of a large brown-black zone exuding from the streaks. What do you define as spot?

Wouldn't be the laws of thermodynamics up on the list?

Dishes serve a very different purpose: sterile working and actually seeing the colonies. Also you will notice that many will not behave the way they are supposed to do (which is also part of the training). Moreover, to my limited knowledge there are only kits for a couple of well-defined groups and even so the identification rate is not stellar. Even well-established one like the enterotube hover at around 90%- again, for well characterized groups. A good microbiological training should cover all the basics and then move on to using kits. In this particular case for instance, it is important to note, how the black dots look like. Are there in the middle of the colonies or (as it supposed to be) diffusing out of the colony (essentially a zone)? Generally the reaction is quite strong with Enterococci and type D streptococci, and if actually have active growth it should be easily distinguishable. What about colony size? What is the color of the colony? Staphylococci tend to be largish white whereas e.g. corynebacteria tend to be smallish yellowish and micrococci whitish grey, each without a brown or black zone. Also regarding the MSA, where the colonies yellow (with a yellow zone) or more orange? Note that I am not primarily a microbiologist and am just saying something from memory. Apparently the training I received a decade or so back was not that bad as I can still remember some stuff.

For starters enterotubes were developed for the identification of Enterobacteriaceae. Thus if you get thrown at with random bacteria it is pretty much useless. Second, the reason for doing these plate assays is train yourself on the technique and the logic behind it and not to stay on the level of a kit user. That being said it would be helpful if you could provide a list of from which you have to select the bacterial species in question, as the combinations in question leave room for quite a number of potential species.

Essentially you are right (I think), though it would be easier if you would be a bit more organized in formulating your thoughts. Plasmid size does not figure in right now. You have the following steps starting from having the plasmid (and insert) purified: restriction, dephposphorylation, ligation, transformation. Each of the steps can be incomplete and you make controls to ensure that that particular step worked. Based on this you are correct to assume that if everything worked perfectly, the plasmids gained from b should be lower than a, but how does it compare to c? Maybe you should give it a try and answer the hypothetical situations that I gave you. Also keep the subsequent steps of a cloning experiment in mind.

You are probably thinking too complicated. Let us take a step back. What are controls for? Answer: they allow us to check what happened at every step of the experiment. Now back to the controls at hand. Non-dephosphorylated vectors can religate and therefore you are correct in assuming that normally you would have a higher number of clones transformed with non-phosphorylated vectors. However, you would also have to look longer to find a clone with the proper insert. Now imagine you conduct experiments in the op and imagine the following scenarios: 1) a has the highest amount, followed by b, then c 2) a has the highest amount, but b and c are equal (though both lower than a) 3) a, b and c are equal What happened at every step? It appears to me that you understood the individual reactions, but you just have to piece the things together. Again, remember that controls are supposed to work in a specific way, but if they don't they hint at something gone wrong.

Several mechanisms pertaining to mRNA stability are known for much longer. However the regulatory role of small RNAs (again, it is not the sole regulator) is a rather novel aspect. Thinking of the regulation as a series of defined switches is often not applicable. Generally you always have a equlibrium reaction. The level of the RISC complex (together with the status of other regulatory elements) regulate the total amount of protein being produced. Each of the circuits can and often are responsive independently from each other. Quite often you will find that a given mRNA is produced (as long as there is no transcriptional repression) and then the due to some factor (or lack of it) the mRNA gets degraded (by RISC and other processes) with only low level of protein translation. Bottom line: things are always a degree of magnitude more complicated than one thinks it is.

Actually this is a given, especially for association studies. For instance, let's say we want to investigate what causes cancer. There are virtually unlimited degrees of freedom, when it comes to the study design. We could for instance look at any type and amount of food, or excercisse, mobile phone usage, etc. In contrast, only a few of these choice actually will be true positives. Since the search space is virtually unlimited there will always be more false than true positives. Of course this is even worse if the study design itself has limitations.

The RISC complex is far from being the only system controlling mRNA stability. It is but one of many layers of regulation. In addition the regulatory cascade can be very complicated and is often not governed by the gene product of the target. They can e.g. be present to maintain certain equlibria, triggered by certain stimuli, be involved in feedback inhibition of metabolites and so on.

Fertilizers are probably less worrisome in terms of toxicity. However think about the ecological impact. E.g. algae growth, sudden biomass increase etc.