Gabaldón T, Huynen M A
NCMLS, CMBI, Center for Molecular and Biomolecular Informatics, University of Nijmegen, Toernooiveld 1, 6525 ED Nijmegen, The Netherlands.
Cell Mol Life Sci. 2004 Apr;61(7-8):930-44. doi: 10.1007/s00018-003-3387-y.
The growing number of completely sequenced genomes adds new dimensions to the use of sequence analysis to predict protein function. Compared with the classical knowledge transfer from one protein to a similar sequence (homology-based function prediction), knowledge about the corresponding genes in other genomes (orthology-based function prediction) provides more specific information about the protein's function, while the analysis of the sequence in its genomic context (context-based function prediction) provides information about its functional context. Whereas homology-based methods predict the molecular function of a protein, genomic context methods predict the biological process in which it plays a role. These complementary approaches can be combined to elucidate complete functional networks and biochemical pathways from the genome sequence of an organism. Here we review recent advances in the field of genomic-context based methods of protein function prediction. Techniques are highlighted with examples, including an analysis that combines information from genomic-context with homology to predict a role of the RNase L inhibitor in the maturation of ribosomal RNA.
全基因组测序数量的不断增加为利用序列分析预测蛋白质功能增添了新的维度。与从一种蛋白质到相似序列的经典知识转移（基于同源性的功能预测）相比，关于其他基因组中相应基因的知识（基于直系同源性的功能预测）能提供有关蛋白质功能的更具体信息，而在基因组背景下对序列的分析（基于背景的功能预测）则能提供有关其功能背景的信息。基于同源性的方法预测蛋白质的分子功能，而基因组背景方法预测其发挥作用的生物学过程。这些互补的方法可以结合起来，从生物体的基因组序列阐明完整的功能网络和生化途径。在此，我们综述基于基因组背景的蛋白质功能预测方法领域的最新进展。文中通过实例突出了相关技术，包括一项将基因组背景信息与同源性相结合的分析，以预测核糖核酸酶L抑制剂在核糖体RNA成熟过程中的作用。
