Godzik A, Jambon M, Friedberg I
Burnham Institute for Medical Research, 10901 N. Torrey Pines Rd., La Jolla, CA 92037, USA.
Cell Mol Life Sci. 2007 Oct;64(19-20):2505-11. doi: 10.1007/s00018-007-7211-y.
The computational prediction of gene and protein function is rapidly gaining ground as a central undertaking in computational biology. Making sense of the flood of genomic data requires fast and reliable annotation. Many ingenious algorithms have been devised to infer a protein's function from its amino acid sequence, 3D structure and chromosomal location of the encoding genes. However, there are significant challenges in assessing how well these programs perform. In this article we explore those challenges and review our own attempt at assessing the performance of those programs. We conclude that the task is far from complete and that a critical assessment of the performance of function prediction programs is necessary to make true progress in computational function prediction.
基因和蛋白质功能的计算预测作为计算生物学的核心任务正在迅速发展。理解海量的基因组数据需要快速且可靠的注释。人们已经设计出许多精巧的算法,用于从蛋白质的氨基酸序列、三维结构以及编码基因的染色体位置推断其功能。然而,评估这些程序的性能存在重大挑战。在本文中,我们探讨了这些挑战,并回顾了我们自己评估这些程序性能的尝试。我们得出结论,这项任务远未完成,对功能预测程序的性能进行批判性评估对于在计算功能预测方面取得真正进展是必要的。