Augmented transitive relationships with high impact protein distillation in protein interaction prediction

Yi Tsung Tang, Hung Yu Kao

研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Predicting new protein-protein interactions is important for discovering novel functions of various biological pathways. Predicting these interactions is a crucial and challenging task. Moreover, discovering new protein-protein interactions through biological experiments is still difficult. Therefore, it is increasingly important to discover new protein interactions. Many studies have predicted protein-protein interactions, using biological features such as Gene Ontology (GO) functional annotations and structural domains of two proteins. In this paper, we propose an augmented transitive relationships predictor (ATRP), a new method of predicting potential protein interactions using transitive relationships and annotations of protein interactions. In addition, a distillation of virtual direct protein-protein interactions is proposed to deal with unbalanced distribution of different types of interactions in the existing protein-protein interaction databases. Our results demonstrate that ATRP can effectively predict protein-protein interactions. ATRP achieves an 81% precision, a 74% recall and a 77% F-measure in average rate in the prediction of direct protein-protein interactions. Using the generated benchmark datasets from KUPS to evaluate of all types of the protein-protein interaction, ATRP achieved a 93% precision, a 49% recall and a 64% F-measure in average rate. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.

原文English
頁(從 - 到)1468-1475
頁數8
期刊Biochimica et Biophysica Acta - Proteins and Proteomics
1824
發行號12
DOIs
出版狀態Published - 2012 12月

All Science Journal Classification (ASJC) codes

  • 分析化學
  • 生物物理學
  • 生物化學
  • 分子生物學

指紋

深入研究「Augmented transitive relationships with high impact protein distillation in protein interaction prediction」主題。共同形成了獨特的指紋。

引用此