Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Switzerland.
Nucleic Acids Res. 2013 Jan;41(Database issue):D808-15. doi: 10.1093/nar/gks1094. Epub 2012 Nov 29.
Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.
全面了解给定细胞中所有蛋白质之间的直接和间接相互作用将是朝着全面描述细胞机制和功能迈出的重要一步。尽管这一目标仍然难以实现，但已经取得了相当大的进展——特别是对于某些模式生物和功能系统。目前，蛋白质相互作用和关联在在线资源中以不同的详细程度进行注释，从原始数据存储库到高度形式化的途径数据库。对于许多应用程序，需要包括低质量数据和/或计算预测在内的所有可用交互数据的全局视图。STRING 数据库（http://string-db.org/）旨在为尽可能多的生物体提供这样的全局视角。已知和预测的关联被评分和整合，从而生成了涵盖超过 1100 个生物体的综合蛋白质网络。在这里，我们描述了 STRING 版本 9.1 的更新，引入了一些改进：（i）我们扩展了对科学文本中交互信息的自动挖掘，现在也包括全文文章；（ii）我们完全重新设计了从一种模式生物到另一种生物转移相互作用的算法；（iii）我们为用户提供了他们网络中观察到的任何功能富集的统计信息。
