利用搜索引擎技术进行蛋白质功能预测。
Using search engine technology for protein function prediction.
作者信息
Chen Ziyang, Cai Zhao, Li Min, Liu Binbin
机构信息
College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China.
出版信息
Int J Bioinform Res Appl. 2011;7(1):101-13. doi: 10.1504/IJBRA.2011.039172.
Prediction of protein function is one of the most challenging problems in the post-genomic era. In this paper, we propose a novel algorithm Improved ProteinRank (IPR) for protein function prediction, which is based on the search engine technology and the preferential attachment criteria. In addition, an improved algorithm IPRW is developed from IPR to be used in the weighted protein?protein interaction (PPI) network. The proposed algorithms IPR and IPRW are applied to the PPI network of S.cerevisiae. The experimental results show that both IPR and IPRW outweigh the previous methods for the prediction of protein functions.
蛋白质功能预测是后基因组时代最具挑战性的问题之一。在本文中，我们提出了一种用于蛋白质功能预测的新算法——改进的蛋白质排序算法（IPR），该算法基于搜索引擎技术和优先连接准则。此外，还从IPR算法发展出一种改进算法IPRW，用于加权蛋白质-蛋白质相互作用（PPI）网络。所提出的IPR和IPRW算法被应用于酿酒酵母的PPI网络。实验结果表明，在蛋白质功能预测方面，IPR和IPRW算法均优于先前的方法。
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