|
|
基于相互作用的蛋白质功能预测
激光生物学报摘要 2007-4
|
王正华, 王秀鹤, 王勇献, 张振慧
（国防科技大学并行与分布处理国家重点实验室, 湖南 长沙 410073）
摘 要:蛋白质功能预测是后基因时代研究的热点问题。基于相互作用的蛋白质功能预测方法目前应用比较广泛，但是当“伙伴蛋白质”（interacting partners)数目较小时，其预测准确率不高。文章从蛋白质相互作用网络入手，结合“小世界网络”特性，有效解决了较小时预测准确率不高的问题。对酵母（Saccharomyces cerevisiae）蛋白质的相互作用网络进行预测，当时其预测准确率比相同条件下的 Global Optimization 方法有一定提高。实验结果表明:该方法能够有效的应用于伙伴蛋白质数目较小时的蛋白质功能预测。
|
|
Inferring Protein Function from Protein-protein Interaction Networks
WANG Zheng-hua , WANG Xiu-he , WANG Yong-xian , ZHANG Zhen-hui
(National Laboratory for Parallel and Distributed Processing, National University
of Deference and Technology , Changsha 410073, Hunan , China)
Abstract：Prediction of protein function is the most challenging problem of the post-genomic era. The methods on the basis of protein-protein interaction networks are widely used at present. But when the interacting partners is small the success rate is decreased. Here we propose a "Small-world Networks"-based algorithm (SWN-BA) to infer protein function from Saccharomyces cerevisiae protein-protein interaction network, and get higher success rate with SWN-BA comparing with Global Optimization (GO) method when . The thought of the "Small-world Networks" can well be used in the study in protein function from protein-protein interaction networks especially when k is small.
|
|
|
|
|
|
Bioinformatics,
sequence analysis; GCG; Life Science News; Drug Discovery.
|
|
