基于相互作用蛋白的语义相似性评估蛋白-蛋白相互作用

IF 0.2 4区生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY International Journal of Data Mining and Bioinformatics Pub Date : 2015-07-01 DOI:10.1504/IJDMB.2015.070842

Guangyu Cui, Byungmin Kim, Saud Alguwaizani, Kyungsook Han

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引用次数: 6

摘要

基因本体(Gene Ontology, GO)由于具有最大和最可靠的基因产物和特征词汇，已被用于估计蛋白质的语义相似性。我们开发了一种新的方法来评估蛋白质-蛋白质相互作用(PPI)利用分支因子和相互作用的蛋白质在氧化石墨烯层次结构的共同祖先的信息含量。我们将该方法与其他基于GO的相似性度量进行了比较评估，评估结果表明我们的方法在大多数GO领域都优于其他方法。

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Assessing protein-protein interactions based on the semantic similarity of interacting proteins

The Gene Ontology (GO) has been used in estimating the semantic similarity of proteins since it has the largest and reliable vocabulary of gene products and characteristics. We developed a new method which can assess Protein-Protein Interactions (PPI) using the branching factor and information content of the common ancestor of interacting proteins in the GO hierarchy. We performed a comparative evaluation of the measure with other GO-based similarity measures and evaluation results showed that our method outperformed others in most GO domains.

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来源期刊

International Journal of Data Mining and Bioinformatics 生物-数学与计算生物学

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Mining bioinformatics data is an emerging area at the intersection between bioinformatics and data mining. The objective of IJDMB is to facilitate collaboration between data mining researchers and bioinformaticians by presenting cutting edge research topics and methodologies in the area of data mining for bioinformatics. This perspective acknowledges the inter-disciplinary nature of research in data mining and bioinformatics and provides a unified forum for researchers/practitioners/students/policy makers to share the latest research and developments in this fast growing multi-disciplinary research area.