Saturday, 7 September 2013

Bioinformatics for geneticists

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.

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