STRING v9.1: protein-protein interaction networks, with increased coverage and integration.
STRING v9.1: protein-protein interaction networks, with increased coverage and integration.
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DOI：
10.1093/nar/gks1094
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发表时间：
2013-01
影响因子：
14.9
通讯作者：
Jensen LJ
中科院分区：
文献类型：
--
作者：
Franceschini A;Szklarczyk D;Frankild S;Kuhn M;Simonovic M;Roth A;Lin J;Minguez P;Bork P;von Mering C;Jensen LJ
完全了解特定细胞中蛋白质之间的所有直接和间接相互作用将是全面描述细胞机制和功能的重要里程碑。虽然这个目标仍然难以实现，但已经取得了相当大的进展，特别是在某些模式生物和功能系统方面。目前，从原始数据存储库到高度形式化的途径数据库，在线资源中对蛋白质相互作用和关联进行了不同程度的详细注释。对于许多应用程序，需要所有可用交互数据的全局视图，包括低质量数据和/或计算预测。STRING数据库（http://string-db.org/）旨在为尽可能多的生物体提供这样一个全球视角。已知的和预测的关联被评分和整合，从而产生覆盖bb101100个生物体的综合蛋白质网络。在这里，我们描述了STRING 9.1版本的更新，介绍了几个改进：(i)我们扩展了科学文本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将相互作用从一个模式生物转移到另一个模式生物的算法；（iii）我们为用户提供在其网络中观察到的任何功能富集的统计信息。
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.
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影响因子：
14.9
作者：
Jensen LJ;Kuhn M;Stark M;Chaffron S;Creevey C;Muller J;Doerks T;Julien P;Roth A;Simonovic M;Bork P;von Mering C
通讯作者：
von Mering C
影响因子：
14.9
作者：
Forbes SA;Bindal N;Bamford S;Cole C;Kok CY;Beare D;Jia M;Shepherd R;Leung K;Menzies A;Teague JW;Campbell PJ;Stratton MR;Futreal PA
通讯作者：
Futreal PA
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
14.9
作者：
Hu Z;Hung JH;Wang Y;Chang YC;Huang CL;Huyck M;DeLisi C
通讯作者：
DeLisi C
影响因子：
7
作者：
Lee, Insuk;Blom, U. Martin;Marcotte, Edward M.
通讯作者：
Marcotte, Edward M.