Applied Bioinformatics

Abstract

The draft sequence of the human genome project was published in 2001 and the number of genes is estimated to be between 20,000 and 25,000. Each human cell, except sperm and eggs, has a complete set of genes. Obviously, however, a blood cell differs in its morphology and physiology from a liver cell. How, therefore, can these differences be explained if all cells have the same genetic material? The answer is simple. Not every gene is transcribed and expressed in every cell. It follows that only those proteins that are required are present in a cell at a given time during the cells life, i.e., the proteome of a cell or tissue is dependent on the cell type and its current state. It also follows that knowledge of the genome and its genes does not suffi ce to explain how a gene, a cell, or an organism works. To understand a complex biological system, one must study the regulation and expression of its genes, the function of expressed proteins, the quantitative occurrence of metabolites, and the effects of gene defects on an organisms phenotype. The study of this complexity is frequently termed Systems biology. Systems biology is a relatively new branch of the life sciences, which tries to understand biological organisms as a whole. Its aim is to obtain an integrated picture of all regulatory processes at all levels, from the genome to the proteome and organelles, and from behavior to the biomechanics of the complete organism. Modern methods for the functional analysis of genomes (functional genomics) are called transcriptomics, proteomics, and metabolomics (Fig. 7.1). These are usually high-throughput procedures that place heavy demands on data-management and -analysis. These approaches are complemented by phenotypic analyses of model organisms and cells in vitro, also in a high-throughput format.