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蛋白质相互作用网络中基于协作的函数预测

Collaboration-based function prediction in protein-protein interaction networks
课程网址: https://videolectures.net/videos/mlsb2010_rahmani_cbf  
主讲教师: Hossein Rahmani
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2010-11-08
课程语种: 英语
中文简介:
我们考虑在蛋白质-蛋白质相互作用(PPI)网络中预测单个蛋白质功能的问题。现有技术假设网络中拓扑上接近的蛋白质往往具有相似的功能。我们假设通过推广这一假设可以获得更好的预测准确性。如果具有一种功能的蛋白质经常与执行另一种功能的蛋白质相互作用,我们称这两个功能为协作。我们的假设是从网络中提取这种功能协作信息并利用它的技术可以产生更好的预测。我们提出并评估了两种这样的技术。对三个酿酒酵母相互作用网络的不同详细程度的比较评估表明,新技术始终优于最先进的功能预测技术,F度量的改进范围为3%至17%。
课程简介: We consider the problem of predicting the functions of individual proteins in protein-protein interaction (PPI) networks. Existing techniques assume that proteins that are topologically close in the network tend to have similar functions. We hypothesize that better predictive accuracy can be obtained by generalizing this assumption. We call two functions collaborative if proteins with one function often interact with proteins performing the other function. Our hypothesis is that techniques that extract such function collaboration information from networks, and exploit it, can yield better predictions.We propose and evaluate two such techniques. A comparative evaluation on three S. cerevisiae interaction networks, at different levels of detail, shows that the new techniques consistently improve over state of the art function prediction techniques, with improvements in F-measure ranging from 3% to 17%.
关 键 词: 蛋白质-蛋白质相互作用(PPI)网络; 功能协作; 功能预测技术
课程来源: vidiolectures
数据采集: 2025-02-25:yuhongrui
最后编审: 2025-02-25:yuhongrui
阅读次数: 1