MOCEA: a multi-objective clustering evolutionary algorithm for inferring protein-protein functional interactions
Pages 1793 - 1794
Abstract
This paper explores the capabilities of multi-objective genetic algorithms to cluster genomic data. We used multiple objective functions not only to further expand the clustering abilities of the algorithm, but also to give more biological significance to the results. Particularly, we grouped a large set of proteins described by a set collection of genomic attributes to infer functional interactions among them. We conducted various computational experiments that demonstrated the proficiency of the proposed method when compared to algorithms that rely on a single biological parameter.
References
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L. Salwinski et al. The Database of Interacting Proteins: 2004 update. Nucleic Acids Research, 32(90001):449--451, 2004.
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Index Terms
- MOCEA: a multi-objective clustering evolutionary algorithm for inferring protein-protein functional interactions
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Published: 08 July 2009
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