Method for Prediction of Protein-Protein Interactions in Yeast Using Genomics/Proteomics Information and Feature Selection

被引：0

作者：

Urquiza, J. M. ^{[1
]}

Rojas, I. ^{[1
]}

Pomares, H. ^{[1
]}

Florido, J. P. ^{[1
]}

Rubio, G. ^{[1
]}

Herrera, L. J. ^{[1
]}

Calvo, J. C. ^{[1
]}

Ortega, J. ^{[1
]}

机构：

[1] Univ Granada, Dept Comp Architecture & Comp Technol, Granada 18017, Spain

来源：

BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1 | 2009年 / 5517卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Protein-protein interaction (PPI) prediction is, one of the main goals in the current Proteomics. This work presents a method for prediction of protein-protein interactions through a classification technique known as Support Vector Machines. The dataset considered is a set of positive and negative examples taken from a high reliability source, from which we extracted a set of genomic features, proposing a similarity measure. Feature selection was performed to obtain the most relevant variables through a modified method derived from other feature selection methods for classification. Using the selected subset of features, we constructed a, support vector classifier that obtains values of specificity and sensitivity higher than 90% in prediction of PPIs, and also providing a confidence score in interaction prediction of each pair of proteins.

引用

页码：853 / 860

页数：8

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