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A regression framework incorporating quantitative and negative interaction data improves quantitative prediction of PDZ domain-peptide interaction from primary sequence.

, , , , , and . Bioinform., 27 (3): 383-390 (2011)

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Network Kernel SVM for microarray classification and gene sets selection., , , and . ISB, page 101-105. IEEE, (2012)A New Support Vector Machine for Multi-class Classification., , and . CIS (1), volume 3801 of Lecture Notes in Computer Science, page 580-585. Springer, (2005)Biased p-norm support vector machine for PU learning., , , and . Neurocomputing, (2014)A class of difference ABS-type algorithms for a nonlinear system of equations., , and . Numerical Lin. Alg. with Applic., 1 (3): 313-329 (1994)Adaptive feature selection via a new version of support vector machine., , , , and . Neural Comput. Appl., 23 (3-4): 937-945 (2013)Laplacian p-norm proximal support vector machine for semi-supervised classification., , , and . Neurocomputing, (2014)Numerical Methods for Unary Optimization., , , and . Encyclopedia of Optimization, Springer, (2009)A Multi-class Classification Algorithm based on Ordinal Regression Machine., , and . CIMCA/IAWTIC, page 810-815. IEEE Computer Society, (2005)Leave-one-out Bounds for Support Vector Regression., and . CIMCA/IAWTIC, page 1061-1066. IEEE Computer Society, (2005)Support Vector Classification with Nominal Attributes., and . CIS (1), volume 3801 of Lecture Notes in Computer Science, page 586-591. Springer, (2005)