Abstract
Genomics has revolutionized research in biological sciences. The reductionist approach of single-molecule analysis is being slowly, but steadily, replaced by global views of the entire cellular machinery. This started with genetics, which turned to determining complete DNA sequences of organisms and is resulting in global comparisons of these sequences to infer their evolutionary past. With the availability of the first complete genome sequences, however, it became obvious that we know very little about how cells work. The problem is that a large number of genes in any genome have functions that are yet unknown, as judged by the lack of obvious phenotype of the corresponding mutants. These “orphan” genes are also not similar at the DNA or protein sequence levels to other genes of known function. The first complete eukaryotic genome, of the yeast Saccharomyces cerevisiae (Goffeau et al., 1996), perhaps the species for which we know most biochemistry, revealed a staggering 40% of genes to which no function could be assigned. Based on this, Oliver called for a systematic approach to the discovery of gene function (Oliver, 1996), which since became known as functional genomics.
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Li, X.J. et al. (2003). Databases and Visualization for Metabolomics. In: Harrigan, G.G., Goodacre, R. (eds) Metabolic Profiling: Its Role in Biomarker Discovery and Gene Function Analysis. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0333-0_16
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DOI: https://doi.org/10.1007/978-1-4615-0333-0_16
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