Computational Biology

A shift in culture Only a decade ago, the ?rst thing a molecular biologist would have had to learn when he or she started the lab work was how to handle pipettes, extract DNA, useenzymesandcloneagene. Now,the?rstthing thatheorsheshould learn is how to handle databases and to extract all the information that is already known about the gene that he or she wants to study. In all likelihood, he or she will ?nd that the gene has already been sequenced from several organisms, that it was recovered in a variety of EST projects, that expression data are available from microarray and SAGE studies, that it was included in linkage studies, that proteomics data are rapidly accumulating, that lists of interacting proteins are being compiled, that domain structure data are available and that it is part of a network of genetic interactions which is intensively modelled. He or she will discover that all this information resides in many di?erent databases with di?erent data formats and with di?erent levels of analyses and linking. Starting to work on this gene will make sense only, if all this information is put together in a project-speci?c manner and set into the context of what is known about related genes and processes. At this point he or she may decide to walk up to the bioinformatics group in house and ask for help with arranging the data in a useful manner.