学术
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k较小时,其预测准确率不高。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k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k≤4时其预测准确率比相同条件下的GO（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。[著者文摘]
文章出处:
《激光生物学报》-2007年16卷4期 -390-393页
栏目信息:
文献标识码:
A
文章编号:
1007-7146（2007）04-0390-04
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 Defense 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 k 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 k ≤4. The thought of the ＂Small-world Networks＂ can well be used in the study of protein function from protein-protein interaction networks especially when k is small,[著者文摘]
Key words:
protein function prediction ; protein-protein interaction ; small-world networks
基金资助:
国家自然科学基金项目（60603054）
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