Evolutionary Optimization of Kernel Weights Improves Protein Complex Comembership Prediction

In recent years, more and more high-throughput data sources useful for protein complex prediction have become available (e.g., gene sequence, mRNA expression, and interactions). The integration of these different data sources can be challenging. Recently, it has been recognized that kernel-based cla...

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Bibliographic Details
Published in:	IEEE/ACM transactions on computational biology and bioinformatics Vol. 6; no. 3; pp. 427 - 437
Main Authors:	Hulsman, M., Reinders, M.J.T., de Ridder, D.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.07.2009 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Artificial Intelligence Bioinformatics biology and genetics Biology computing Classifier design and evaluation Evolution, Molecular Evolutionary computation evolutionary computing and genetic algorithms Kernel Large-scale systems Linear Models Models, Genetic Multiprotein Complexes - chemistry Nonlinear Dynamics Optimization methods Protein engineering Reproducibility of Results ROC Curve Sequences Studies Support vector machine classification Support vector machines
ISSN:	1545-5963, 1557-9964, 1557-9964
Online Access:	Get full text
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