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Re: [tlug] Open Access Journals
- Date: Fri, 4 Apr 2014 00:08:39 +0800
- From: Raymond Wan <firstname.lastname@example.org>
- Subject: Re: [tlug] Open Access Journals
- References: <53292BF2.email@example.com> <CAAhy3dsA3yJ+dhP8y5AnkDm0Rhepfe6TyxXwENkiWtrqtqAgYQ@mail.gmail.com> <firstname.lastname@example.org> <email@example.com> <firstname.lastname@example.org> <email@example.com> <firstname.lastname@example.org> <email@example.com> <firstname.lastname@example.org> <CAAhy3ds-Tfno8KrsexFnB3CracrTYUpM962HD4jETsVaVAKxhA@mail.gmail.com> <email@example.com>
On Mon, Mar 31, 2014 at 10:17 AM, Stephen J. Turnbull <firstname.lastname@example.org> wrote: > AIUI, much of bioinformatics is about *historical* DNA, which is > "complex" rather than "chaotic". Unfortunately I don't really know > enough to define those terms, basically though we're trying to > understand past evolution at the DNA level rather than predict the > future evolution, and then DNA is basically a digital computer -- > matching DNA to phenotype may be "sloppy", but the DNA itself can be > described "precisely", although it is very complex. So useful > patterns not justifiable by existing theory, and reproducible > anomolies contradicting existing theory, can occur in bioinformatics. I can't comment about what you said before about economics, but what you said above about bioinformatics is fairly accurate. > So I personally (but not intimately familiar with your field) would > tend to be more tolerant of research "lacking discipline" in > bioinformatics than in economics, simply because only a multimodal > genius like Arrow or Einstein can start to see how to gather the > threads of discussion into a coherent discipline of complexity. I jumped into the life sciences a bit late but I always envisioned research to be about being interested in some phenotype, coming up with some experiment to verify it, and if you're right, write it up. Now, it's almost reached a point in bioinformatics where we don't know what we're looking for...so let's throw it into a piece of software (i.e., a machine learning algorithm for example) -- it tells us which genes out of the thousands that were examined are interesting in a statistically significant way, and then we write a paper about it. It's hard to say how much better bioinformatics is compared to what you describe about economics... Ray
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