Despite
a relatively short existence, bioinformatics has always seemed an unusually
multidisciplinary field. Fifteen years ago, when sequence data were still
scarce and only a small fraction of the power of today’s pizza-box
supercomputers was available, bioinformatics was already entrenched in a
diverse array of topics. Database development, sequence alignment, protein
structure prediction, coding and promoter site identification, RNA folding, and
evolutionary tree construction were all within the remit of the early
bioinformaticist.1,2. To address these problems, the field drew from the
foundations of statistics, mathematics, physics, computer science, and of
course, molecular biology. Today, predictably, bioinformatics still reflects
the broad base on which it started, comprising an eclectic collection of
scientific specialists. As a result of its inherent diversity, it is difficult
to define the scope of bioinformatics as a discipline. It may be even fruitless
to try to draw hard boundaries around the field. It is ironic, therefore, that
even now, if one were to compile an intentionally broad list of research areas within
the bioinformatics purview, it would often exclude one biological discipline
with which it shares a fundamental basis: Genetics. On one hand, this seems
difficult to believe, since the fields share a strong common grounding in
statistical methodology, dependence on efficient computational algorithms,
rapidly growing biological data, and shared principles of molecular biology. On
the other hand, this is completely understandable, since a large part of
bioinformatics has spent the last few years helping to sequence a number of
genomes, including that of man. In many cases, these sequencing projects have
focused on constructing a single representative sequence—the consensus—a
concept that is completely foreign to the core genetics principles of
variability and individual differences. Despite a growing awareness of each
other, and with a few clear exceptions, genetics and bioinformatics have managed
to maintain separate identities.
Geneticists
need bioinformatics. This is particularly true of those trying to identify and
understand genes that influence complex phenotypes. In the realm of human
genetics, this need has become particularly clear, so that most large
laboratories now have one or two bioinformatics ‘specialists’ to whom other lab
members turn for computing matters. These specialists are required to support a
dauntingly wide assortment of applications: typical queries for such people
might range from how to find instructions for accessing the internet, to how to
disentangle a complex database schema, to how to optimize numerically intensive
algorithms on parallel computing farms. These people, though somewhat scarce, are
essential to the success of the laboratory.
0 comments:
Post a Comment