Mellor Joseph C, Yanai Itai, Clodfelter Karl H, Mintseris Julian, DeLisi Charles
Bioinformatics Graduate Program and Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
Nucleic Acids Res. 2002 Jan 1;30(1):306-9. doi: 10.1093/nar/30.1.306.
The current deluge of genomic sequences has spawned the creation of tools capable of making sense of the data. Computational and high-throughput experimental methods for generating links between proteins have recently been emerging. These methods effectively act as hypothesis machines, allowing researchers to screen large sets of data to detect interesting patterns that can then be studied in greater detail. Although the potential use of these putative links in predicting gene function has been demonstrated, a central repository for all such links for many genomes would maximize their usefulness. Here we present Predictome, a database of predicted links between the proteins of 44 genomes based on the implementation of three computational methods--chromosomal proximity, phylogenetic profiling and domain fusion--and large-scale experimental screenings of protein-protein interaction data. The combination of data from various predictive methods in one database allows for their comparison with each other, as well as visualization of their correlation with known pathway information. As a repository for such data, Predictome is an ongoing resource for the community, providing functional relationships among proteins as new genomic data emerges. Predictome is available at http://predictome.bu.edu.
当前基因组序列的大量涌现催生了能够理解这些数据的工具。最近,用于建立蛋白质之间联系的计算方法和高通量实验方法不断涌现。这些方法实际上起到了假设生成器的作用,使研究人员能够筛选大量数据,以检测出有趣的模式,进而进行更深入的研究。尽管这些假定联系在预测基因功能方面的潜在用途已得到证实,但一个包含许多基因组所有此类联系的中央储存库将使其效用最大化。在此,我们展示了Predictome,这是一个基于三种计算方法(染色体邻近性、系统发育谱分析和结构域融合)以及蛋白质-蛋白质相互作用数据的大规模实验筛选,构建的44个基因组蛋白质之间预测联系的数据库。将来自各种预测方法的数据整合在一个数据库中,便于相互比较,也能直观呈现它们与已知通路信息的相关性。作为此类数据的储存库,Predictome是一个不断更新的社区资源,随着新的基因组数据出现,提供蛋白质之间的功能关系。可通过http://predictome.bu.edu访问Predictome。