PPIevo: Protein-protein interaction prediction from PSSM based evolutionary information

被引:117
作者
Zahiri, Javad [1 ]
Yaghoubi, Omid [2 ]
Mohammad-Noori, Morteza [3 ]
Ebrahimpour, Reza [4 ]
Masoudi-Nejad, Ali [1 ]
机构
[1] Univ Tehran, Lab Syst Biol & Bioinformat LBB, Inst Biochem & Biophys, Tehran, Iran
[2] Shamsipour Tech & Profess Univ, Dept Comp Engn, Tehran, Iran
[3] Univ Tehran, Coll Sci, Sch Math Stat & Comp Sci, Tehran, Iran
[4] Shahid Rajaee Teacher Training Univ, Dept Elect & Comp Engn, Brain & Intelligent Syst Res Lab, Tehran, Iran
关键词
Protein-protein interaction map; Protein interaction networks; Computational intelligence; Machine learning; Position-specific scoring matrix; MOLECULAR INTERACTION DATABASE; DATA INTEGRATION; DATASETS; NETWORKS; PAIRS;
D O I
10.1016/j.ygeno.2013.05.006
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Protein-protein interactions regulate a variety of cellular processes. There is a great need for computational methods as a complement to experimental methods with which to predict protein interactions due to the existence of many limitations involved in experimental techniques. Here, we introduce a novel evolutionary based feature extraction algorithm for protein-protein interaction (PPI) prediction. The algorithm is called PPIevo and extracts the evolutionary feature from Position-Specific Scoring Matrix (PSSM) of protein with known sequence. The algorithm does not depend on the protein annotations, and the features are based on the evolutionary history of the proteins. This enables the algorithm to have more power for predicting protein-protein interaction than many sequence based algorithms. Results on the HPRD database show better performance and robustness of the proposed method. They also reveal that the negative dataset selection could lead to an acute performance overestimation which is the principal drawback of the available methods. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:237 / 242
页数:6
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