Evaluation of machine learning algorithms on protein-protein interactions

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• Protein-protein interactions are important for the majority of biological processes. A significant number of computational methods have been developed to predict protein-protein interactions using proteins' sequence, structural and genomic data. Hence, this fact motivated us to perform a comparative study of various machine learning methods, training them on the set of known protein-protein interactions, using proteins' global and local attributes. The results of the classifiers were evaluated through cross-validation and several performance measures were computed. It was noticed from the results that support vector machine outperformed other classifiers. This fact has also been established through statistical test, called Wilcoxon rank sum test, at 5% significance level.

Ämnesord

NATURVETENSKAP  -- Biologi -- Bioinformatik och systembiologi (hsv//swe)

NATURAL SCIENCES  -- Biological Sciences -- Bioinformatics and Systems Biology (hsv//eng)

LANTBRUKSVETENSKAPER  -- Bioteknologi med applikationer på växter och djur -- Genetik och förädling inom lantbruksvetenskap (hsv//swe)

AGRICULTURAL SCIENCES  -- Agricultural Biotechnology -- Genetics and Breeding in Agricultural Sciences (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

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