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If a bit of uncataloguged cruft on your storage is going to destroy your brain then you must be a bit of a snowflake. Smart human beings can cope with web sites like this https://viralzone.expasy.org/ and remember vast swathes of it. Check in your nerd card right now if your personal data has beaten you.

More data: Haplotype "KL-VS" refers to the V and S alleles of the SNPs respectively. It contains six sequence variants in complete linkage disequilibrium, two of which result in amino acid substitutions F352V (rs9536314) and C370S (rs9527025, not on 23andme btw). It is present in 15% of Caucasians.

More data: Haplotype "KL-VS" refers to the V and S alleles of the SNPs respectively. It contains six sequence variants in complete linkage disequilibrium, two of which result in amino acid substitutions F352V (rs9536314) and C370S (rs9527025, not on 23andme btw). It is present in 15% of Caucasians.

Since my experience is primarily in molecular and computational biology, my opinions are obviously biased towards those fields. I have worked in both academia and industry (i.e. >15 years of "Science" experience with 9 years at the PhD level). In my opinion, you should be concentrating on these science skills in upper grade level high school (11-12 grades, preferably just 12).

1) Really get to know MS Office or some other package of word processing (with references support, like Endnote), spreadsheet, and presentation software. You will need a good understanding of the word processor to write grants, reports, and manuscripts. A good understanding of the spreadsheet to organize and analyze your data, with special attention on doing correct statistical analysis. A good understanding of the presentation software for ... presentations. Macs or Windows since it doesn't matter.

2) Really know how to use websites such as http://www.ncbi.nlm.nih.gov/ and http://expasy.org/. The biological science world revolves around biomolecule and biopolymer databases. Then, make them find manuscripts in http://www.ncbi.nlm.nih.gov/pubmed and evaluate them. They also need to learn to evaluate the quality of the information that they find.

3) Make them do journal club. That will hit all levels of Bloom's taxonomy, is student-centered, and buzzword compliant!

Other skills that maybe useful:

3) Entering, searching, and retrieving information from a SQL-like database. Oracle, MySQL, or PostgreSQL servers are everywhere in both academia and industry. Maybe industry has enough resources to create a frontend for their scientists, but most likely they will have to wait for the comuputer analyst group to provide the data you want. Better to ask for read access and do it yourself. Any operating system can be used to access the data. MySQL and PostgreSQL are well supported in Linux.

4) Industry is moving to Lab Information Management Systems (LIMS) and large data generating academic labs are also using LIMS. I don't know if there are free/low-cost LIMS software available, but this would be extremely nice exposure considering most universities won't have such a system for undergraduates. Most LIMS are web-based so it really doesn't matter about the front-end. The back-end is probably Linux or Windows Server.

5) In academia, knowing Linux/Unix/BSD is very useful as most academic software packages are made to run on a Unix-like OS. MacOS X support is actually pretty decent for academic software due to its BSD underpinnings. CygWin is a must if you want to run on Windows. Academics program for the computers that they have, and they mostly have Macs and Unix-like systems.

5) Programming languages that are used extensively by computational biologists are C/C++, PERL, PYTHON, JAVA, and Fortran (more legacy now). From what I saw, PERL and PYTHON dominate on the bioinformatics side.

As for hardware/OS...
For computational biology or computers in biology, Windows is winning that market share. Macs are pretty much only found in academia and mainly for MS Office. They can be used as front-ends obviously, but the general trend of specialized software is to run on XP, for now. I don't know how many science software developers have moved their code to support Win7 natively, but probably not many as these companies are rather slow in adopting new tech. Still, obtaining these licenses is pretty much impossible for a high school. I doubt even the district could find the budget for them.

Setting a Linux cluster for computational number crunching is seen very often in academia and probably in industry, too. So, maybe you can salvage some of the older computers and turn them into a small computational cluster. However, setting up things like this may be impractical with your IT department...

Overall, I think it is very ambitious to provide "real world" science

Okay, let me explain for you non-biochemist computer guys what this means. Take a computer, break it down into the smallest possible parts you can. I'm not talking about the hard drive/motherboard/case level. I'm talking about the level of transistors, resistors, ICs, connectors, motors, and the little blue LED that blinks whenever your hard drive spins. Now catalog everything. Keep a record of what you found where, and how many you found (eg, you found a laser in the DVD drive but not in the motherboard). So now you have a parts list, and a good idea of what parts to expect where. If you start finding unexpected things in unexpected places (like a SCSI connector on your video card, or an audio out port on one of your DIMMs), that tells you something is wrong.

Take a look at the database entry for something common like glucose. It's got

1. a brief, high-level description of the chemical
2. details about the chemistry
3. where it's found in the body
4. details about how much of it was found in what parts of the body based on various studies that have already been done
5. disorders it's linked to (eg, diabetes)
6. where to go for more information

Now what's missing is a lot of information about the connections, so technically this isn't really a map (because it's missing relational data), but a catalog. We need to know how each chemical turns into another, and what does the conversion. It's kinda like having a complete parts list for the computer, but not knowing how most of the parts fit together, nor how many volts and amps to run through the wires. Some of these connections we already know. I have a very large poster on my wall illustrating the more common chemical pathways in various organisms. It's not nearly as complete as this catalog in terms of chemicals, but it's got a lot of connections.

The connections are what's really useful. To continue the computer analogy, if you know that the blue LED connects to the hard drive, then if you don't see the blue light blink, then there's probably something wrong with the hard drive. A significant number of drugs aren't active in the form that you take them. They become active when the body (usually in the liver) converts them from the delivery form to the active form. But some people, because of their genetic makeup, convert the drugs differently. They turn them into different metabolites. These metabolites might be totally inactive, or even toxic in some cases. So if you know the connecting system, you can put a drug in, look for what metabolites result, and determine whether or not that person should continue taking the drug.

All available genetic data (and protein data) from every sequenced organism has always been publicly available. Whether it's due to requirements by publishers of the journals that they publish their analysis in, a requirement of their funding agencies, or for the mere goal of sharing their data with the global scientific community.

Gene sequence databases have been around since 1981:
EMBL: http://www.ebi.ac.uk/embl/
GenBank: http://www.ncbi.nlm.nih.gov/
DDBJ: http://www.ddbj.nig.ac.jp/
HUGO: http://www.gene.ucl.ac.uk/nomenclature/
JGI: http://www.jgi.doe.gov/

Protein sequence/structure data is also publicly available:
Expasy: http://ca.expasy.org/
PDB: http://www.pdb.org/

Their statement "Google is guilty of biopiracy because a searchable database could make it easier for private genetic information to be abused" is flawed on many levels.. and is merely an attempt at media hype.

A - If the genetic data is private (ie. industry funded and not shared with the global scientific community), how will Google get access to it?
B - Searchable databases that contain private/public genetic information have existed since before most other types of searchable databases.
C - Sharing data from biological analyses (whether genetic sequence data, protein sequence data, gene expression data, protein structure data, etc.) is an important aspect of understanding the underlying mechanisms of biological systems.

Many of the medical advances that we've seen these past couple decades have resulted directly from the fact that biological data has been publicly available... facilitating collaborations beyond borders and beyond disciplines.

I look forward to Google's role in facilitating access to this information, and look forward to applying it in future research projects.

Ryan

Although it is mainly protein oriented, there are several molecular tools available at ExPASy that I use a lot.

Also, VectorNTI is now free if you join their user group. It's a really powerful suite for plasmid design and molecular analysis.

A real feat would be robots that could self replicate with their only material inputs being, say, raw minerals and energy. That would be closer to what bacteria do.

Evolution works by the frequencies of different genes and gene sequences changing due to changing external conditions.

The post I replied to (was it yours, AC?) was trying to make the case that, because some of the precise phenomenologies had not been quite understood, it means that all of evolution is nonsense.

Evolution works by the frequencies of different genes and gene sequences changing due to changing external conditions.

The post I replied to (was it yours, AC?) was trying to make the case that, because some of the precise phenomenologies had not been quite understood, it means that all of evolution is nonsense.

Life may very well be possible with many different sets of molecules.

After the Miller-Urey experiment, Stanley's so far spent the rest of his life trying to make the other necessaries, and has so far discovered that (1) you can't; and (2) the conditions for his original experiment have never existed.

He has discovered no such thing as (1), any more than the thousands of man hours that went into attempts to fly prior to the Wright brothers proved that flight couldn't be achieved.

Stanley is attempting to compress phenomenon that occurred over millions of years and in oceans of water into a test tube. That may or may not be possible.

Life may very well be possible with many different sets of molecules.

After the Miller-Urey experiment, Stanley's so far spent the rest of his life trying to make the other necessaries, and has so far discovered that (1) you can't; and (2) the conditions for his original experiment have never existed.

He has discovered no such thing as (1), any more than the thousands of man hours that went into attempts to fly prior to the Wright brothers proved that flight couldn't be achieved.

Stanley is attempting to compress phenomenon that occurred over millions of years and in oceans of water into a test tube. That may or may not be possible.

Okay, it's a pretty cool idea and it goes one step further than what my friends and I (grad students in biology or chemistry) have done on our own by putting useful biochemistry tools on a CD for when we travel. But Rasmol?! It's antiquidated and was replaced by Protein Explorer, a Rasmol derivative, three or four years ago. If you want a free, compact, powerful, and reasonably easy-to-use program that can be run on linux/mac/windows for viewing macromolecular structures then you use Deep View
Swiss-PdbViewer. It can do a lot of what the molecular visualization programs we actually use to build protein structures (eg O, Xtalview) can do, plus you can use it to generate good-quality images by using POV-Ray.

Hi ho, link nazi here. PLEASE make your URLs into links. Not only is it harder to copy/paste the url, Slashdot's word-wrap breaker will insert random spaces into long "words", thus breaking the URL.

You too can do your part to save the world, one <a href= at a time!

Here's the spider farming article.

A lot of it is open source; unfortunately a lot of it also epitomizes what's wrong with non-commercial software. You might have just one small group, one lab, or even just one guy who's little baby that program is. For what I've used, the majority of the open source software and freeware runs on unix, not windows, although there is a growing commitment to linux and windows that will become dominant in the next couple of years. Most of it runs. Sort of. If you're willing to fight with it. The only thing worse than the user interface is the manual, if one exists at all (although exceptions exist, such as Deep View Swiss PDB Viewer). While I'd agree that many biologists have poor computer skills, that's rapidly changing as more and more the problem is data interpretation as opposed to data acquisition. There are many subdisciplins where a good percentage of the biologists also possess some ability for computer programming (or at least script writing) just becuase that's the only way to force the software to work. I'd also agree that a CD package with documentation on a popular set of programs would be great, but that's complicated by the fact that the geneticists don't do biochemistry who don't do cell biology etc. That and getting a bunch of scientists together on something like this is like herding cats.

We don't need some mad scientist in jersey to cook up funky chemicals that make bitter into sweet, mother nature already did it a long time ago with the miracle berry.

Dr. Stemmer argued that it would also aid other researchers by making more DNA sequences available. With the current uncertainty about patents, some companies have refused to reveal sequences they have deciphered out of fear that they will lose the rights to them.

Feh. Let them keep their secrets. As sequencing technology improves (I work in crystallography, a related field. Sequencing is improving rapidly in both accuracy and speed.) More and more sequences will be deciphered in an academic context and released into the public domain. Public science will suffer far more from companies trying to exert some kind of intellectual property rights over this genetic information that it will from academics having to do the work of sequencing.

Secondly, the whole concept is an insult. The company that copyrights the music (or, whoever owns the copyright on the music - another poster was keen to raise this as a question) owns only the music, not the sequence the music was derived from. If I'm going to use that sequence in any kind of peer-reviewed publication, I will have to make it available to other scientists, free of charge. Now, I presumably purchased some kind of access rights to the sequence, which included (a probably unenforceable) clause not to redistribute the sequence itself; this will likely prevent me from publishing in any reputable journal. Such non-redistribution agreements are common when scientists acquire physical research tools from industry - if I purchase a plasmid (that's a tiny piece of DNA that replicates in bacteria; most antibiotic resistance in bacteria is conferred from plasmids) I have to agree not to take that plasmid, copy it myself, and sell it or give it away. I'm free to talk about the sequence of the plasmid, however. So, any scientist who purchased access to your digital music would have to sign a non-disclosure agreement regarding the DNA the music converted into, since that DNA sequence itself is not subject to copyright. If, however, someone else (who hadn't signed such an agreement) acquired the DNA sequence, and dumped it in SwisProt, it would be IMPOSSIBLE to tell where it came from originally; unless you "watermarked" each DNA sequence you distributed with errors of some kind.

Of course, this raises fundamental questions of the validity of digital copyright law, which amounts to copyrighting integers. I can write a program (which I copyright) that converts some particular string of babble (which I also copyright) into the text of War and Peace. Do I now own the copyright to War and Peace? Obviously not! I can distribute, and charge money for "wnpcmake.exe", but I have no claims on the OUTPUT that wnpcmake.exe always produces. If wnpcmake.exe happens to produce content owned by someone else, say, "The Ground Beneath her Feet" by Salman Rushdie, then I'm in violation of Rushdie's copyright. I have no claims of my own.

The copyright is on some real world thing, not on any particular digital representation. So, Amgen might own "Human liver fatty acid binding protein cancer-prone allele in C minor," which happens to map somehow to the sequence of that allele (an allele is a particular sequence/variant of a gene); they own the right to perform that piece of music, they own the right to distribute recordings of that music (digital or otherwise) and so forth. But, they can't write some program that converts War and Peace INTO this piece of music (or vice versa) and claim that they own War and Peace. Likewise, just because a DNA sequence HAPPENS to convert to their music, under some set of rules THEY have devised, cannot reasonably be expected to grant them rights over the sequence.

Note that I am not a lawyer, and can speak only for what is logical and sensible. To the extent that law may deviate from sanity, I cannot comment. Since patenting DNA sequences flies in the face of all reason anyway, I pretty much expect to be unpleasantly surprised.