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This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization. Applications in genomics, proteomics, systems biology, evolution and text mining are also shown. Supervised classification, clustering and probabilistic graphical models for bioinformatics are reviewed. A review ofdoi:10.1093/bib/bbk007 pmid:16761367 fatcat:4oss26occvhkjnetcr3sesnkcu