Suppr超能文献

基于蛋白质-蛋白质相互作用网络和基因表达数据整合来识别蛋白质复合物。

Identifying protein complexes based on the integration of PPI network and gene expression data.

作者信息

Chen Weijie, Li Min, Wu Xuehong, Wang Jianxin

机构信息

School of Information Science and Engineering, Central South University, Changsha 410083, China.

出版信息

Int J Bioinform Res Appl. 2015;11(1):30-44. doi: 10.1504/IJBRA.2015.067337.

Abstract

Identification of protein complexes is crucial to understand principles of cellular organisation and predict protein functions. In this paper, a novel protein complex discovery algorithm IPCIPG is proposed based on the integration of Protein-Protein Interaction network (PPI network) and gene expression data. IPCIPG is a local search algorithm which has two versions: IPCIPG-n for identifying non-overlapping clusters and IPCIPG-o for detecting overlapping clusters. The experimental results on the yeast PPI network show that IPCIPG can identify protein complexes with specific biological meaning more effectively, precisely and comprehensively than six other algorithms: HUNTER, HC-PIN, CMC, SPICi, MOCDE and MCL.

摘要

蛋白质复合物的识别对于理解细胞组织原理和预测蛋白质功能至关重要。本文基于蛋白质-蛋白质相互作用网络(PPI网络)和基因表达数据的整合,提出了一种新型蛋白质复合物发现算法IPCIPG。IPCIPG是一种局部搜索算法,有两个版本:用于识别非重叠簇的IPCIPG-n和用于检测重叠簇的IPCIPG-o。在酵母PPI网络上的实验结果表明,与其他六种算法(HUNTER、HC-PIN、CMC、SPICi、MOCDE和MCL)相比,IPCIPG能够更有效、精确和全面地识别具有特定生物学意义的蛋白质复合物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验