1.2 What Can Bioinformatics Do?

5

of unknown sequences with known ones can also help to elucidate function; both

parts are concerned with the search for patterns or regularities—which is indeed the

core of all scientific work. It seems fortunate (for scientists) that life is in some sense

encapsulated in such a highly formalized object as a sequence of symbols (a string).

The requirement of entire genomes to feed this search has led to tremendous

advances in the technology of rapid sequencing, which, in turn, has put new demands

on informatics for interpreting the raw output of a sequencer to generate a DNA

sequence. If that is the message, then functional genomics is concerned with the

meaning of the message and, in turn, this has led to the experimental analysis of

the RNA transcripts (the transcriptome) and the repertoire of expressed proteins (the

proteome), each of which presents fresh informatics challenges. They have them-

selves spawned interest in the products of protein activity—saccharides (glycomics),

lipids (lipidomics), and metabolites (metabolomics). All these “-omics”, including

the integrative phenomics, are considered to be part of bioinformatics and are cov-

ered in this book. Mindful of the need to keep its length within reasonable bounds,

chemical genomics (or chemogenomics), defined as the use of small molecules to

study the functions of the cell at the genome level (including investigation of the

effects of such molecules on gene expression), although closely related to the other

topics, is not covered. Computational biology (defined as the application of quantita-

tive and analytical techniques to model biological systems) is only covered via a brief

consideration of the virtual living organism. Also in order to keep the length of this

book within reasonable bounds, the impressive attempts of Holland, Ray, and others

to model some characteristic features of life—speciation and evolution—entirely in

silico using digital organisms (i.e., computer programs able to self-replicate, mutate,

etc.) are not covered.

Many bioinformaticians wonder what is the relation of their field to systems biol-

ogy , which “aims to understand biological behaviour at the systems level through an

abstract description in terms of mathematical and computational formalisms”. ⁵ As

far as can be discerned (“definitions” abound), it is really a subset of bioinformatics

dealing especially with modelling and perhaps constituting the intersection of bioin-

formatics with computational biology. If emphasis is placed on the abstract descrip-

tion aspect, systems biology would appear to be the same as what was previously

called analytical biology. The supreme challenge is to model the main information-

processing centre of a living organism, notably the brain. It seems perfectly rea-

sonable to include neurophysiology within bioinformatics, since it deals with how

information is generated, transmitted, received, and interpreted in the brain; that is, it

corresponds precisely with our definition given above, although it is often considered

to be a vast field in its own right. This is even more true of the science of human

communication and cognition, which has, regrettably, to be left aside in this book.

Aside from whole genome sequencing, another outcome of high-throughput biol-

ogy is the experimental determination of interactions between objects (i.e., between

5 Kolch et al. (2005).