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Selecting negative samples for PPI prediction using hierarchical clustering methodology
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نویسنده
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urquiza j.m. ,rojas i. ,pomares h. ,herrera j. ,florido j.p. ,valenzuela o.
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منبع
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journal of applied mathematics - 2012 - دوره : 2012 - شماره : 0
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چکیده
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Protein-protein interactions (ppis) play a crucial role in cellular processes. in the present work,a new approach is proposed to construct a ppi predictor training a support vector machine model through a mutual information filter-wrapper parallel feature selection algorithm and an iterative and hierarchical clustering to select a relevance negative training set. by means of a selected suboptimum set of features,the constructed support vector machine model is able to classify ppis with high accuracy in any positive and negative datasets. copyright © 2012 j. m. urquiza et al.
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آدرس
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department of computer architecture and computer technology,university of granada, Spain, department of computer architecture and computer technology,university of granada, Spain, department of computer architecture and computer technology,university of granada, Spain, department of computer architecture and computer technology,university of granada, Spain, department of computer architecture and computer technology,university of granada, Spain, department of applied mathematics,university of granada, Spain
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Authors
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