Bork P, Dandekar T, Diaz-Lazcoz Y, Eisenhaber F, Huynen M, Yuan Y
European Molecular Biology Laboratory, Meyerhofstr. 1, Heidelberg, PF 10.2209, Germany.
J Mol Biol. 1998 Nov 6;283(4):707-25. doi: 10.1006/jmbi.1998.2144.
Predicting function from sequence using computational tools is a highly complicated procedure that is generally done for each gene individually. This review focuses on the added value that is provided by completely sequenced genomes in function prediction. Various levels of sequence annotation and function prediction are discussed, ranging from genomic sequence to that of complex cellular processes. Protein function is currently best described in the context of molecular interactions. In the near future it will be possible to predict protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. The analysis of such higher levels of function description uses, besides the information from completely sequenced genomes, also the additional information from proteomics and expression data. The final goal will be to elucidate the mapping between genotype and phenotype.
使用计算工具从序列预测功能是一个高度复杂的过程,通常是针对每个基因单独进行的。本综述重点关注全基因组测序在功能预测中所提供的附加价值。文中讨论了从基因组序列到复杂细胞过程的不同层次的序列注释和功能预测。目前,蛋白质功能最好在分子相互作用的背景下进行描述。在不久的将来,有可能在诸如基因表达调控、代谢途径和信号级联等高阶过程的背景下预测蛋白质功能。除了来自全基因组测序的信息外,对这种更高层次功能描述的分析还利用了蛋白质组学和表达数据的附加信息。最终目标将是阐明基因型与表型之间的映射关系。