Suppr超能文献

一种基于连通亲和团扩展(CACE)的新型蛋白质复合物识别算法。

A novel protein complex identification algorithm based on Connected Affinity Clique Extension (CACE).

作者信息

Li Peng, He Tingting, Hu Xiaohua, Zhao Junmin, Shen Xianjun, Zhang Ming, Wang Yan

出版信息

IEEE Trans Nanobioscience. 2014 Jun;13(2):89-96. doi: 10.1109/TNB.2014.2317755. Epub 2014 Apr 24.

Abstract

A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity which is inferred from protein complexes is interpreted as the reliability and possibility of interaction. The protein interaction network is constructed as a weighted graph, and the weight is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effectively and accurately when compared with other state-of-art algorithms CPM and IPC-MCE.

摘要

本文提出了一种基于连通亲和团扩展(CACE)的新颖算法,用于在蛋白质相互作用网络中挖掘重叠功能模块。在这种方法中,从蛋白质复合物推断出的蛋白质连通亲合度值被解释为相互作用的可靠性和可能性。蛋白质相互作用网络被构建为一个加权图,权重取决于连通亲和系数。我们的CACE在两个测试数据集上的实验结果表明,与其他现有算法CPM和IPC-MCE相比,CACE能够更有效、准确地检测功能模块。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验