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交互式蛋白质组学的生物信息学分析

Bioinformatics analysis for interactive proteomics.

作者信息

Chen Yu, Xu Dong

机构信息

Monsanto Company, St. Louis, Missouri.

University of Missouri-Columbia, Columbia, Missouri.

出版信息

Curr Protoc Protein Sci. 2005 Dec;Chapter 25:25.1.1-25.1.14. doi: 10.1002/0471140864.ps2501s42.

Abstract

High-throughput protein-protein interaction data are becoming a foundation for new biological discoveries. A major challenge is to manage, analyze, and model these data. In this unit several databases are described that are used to store, query, and visualize protein-protein interaction data. Comparison between experimental techniques reveals that each high-throughput technique has its limitations in detecting certain types of interactions; however, the techniques are generally complementary. In silico prediction methods for protein-protein interactions can expand the scope of experimental data and increase the confidence of certain interactions. Use of protein-protein interaction networks, preferably integrating them with other types of data, allows assignment of cellular functions to novel proteins and derivation of new biological pathways. As demonstrated in this unit, bioinformatics can be used to transform protein-protein interaction data from noisy information into knowledge of cellular mechanisms.

摘要

高通量蛋白质-蛋白质相互作用数据正成为新的生物学发现的基础。一个主要挑战是管理、分析和模拟这些数据。本单元介绍了几个用于存储、查询和可视化蛋白质-蛋白质相互作用数据的数据库。实验技术之间的比较表明,每种高通量技术在检测某些类型的相互作用方面都有其局限性;然而,这些技术通常是互补的。蛋白质-蛋白质相互作用的计算机预测方法可以扩展实验数据的范围,并增加对某些相互作用的置信度。使用蛋白质-蛋白质相互作用网络,最好是将它们与其他类型的数据整合,能够为新蛋白质赋予细胞功能,并推导出新的生物学途径。如本单元所示,生物信息学可用于将蛋白质-蛋白质相互作用数据从嘈杂的信息转化为细胞机制的知识。

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