The hub prediction model, HUBCENTRE, is the first one of its kind which enables the user to know whether a target protein is hub or non-hub based on the primary sequence information alone. The prediction of protein"hubs" was done using physiochemical, thermodynamic and conformational properties of amino acid residues from amino acid sequence. Our prediction results show that meaningful amino acid features can produce signature features for differentiating hubs from non-hubs. The classical classification method, Support Vector Machines (SVM), is used to develop a tool to discriminate between hub and non hub proteins.

Funding from Department of Information Technology,Govt. of India, (DIT/R&D/B10/15(23)2008, dated 07/09/2010), is acknowledged.

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Registered

2015-06-09