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Machine learning in bioinformatics
Pedro Larrañaga (University of the Basque Country), Borja Calvo (University of the Basque Country, University of Havana), Roberto Santana (Universidad Complutense de Madrid, Universidad Politécnica de Madrid), Concha Bielza (University of the Basque Country), Josu Galdiano (University of the Basque Country), Iñaki Inza (University of the Basque Country), Jose Antonio Lozano (University of the Basque Country), Rubén Armañanzas (University of the Basque Country), Guzmán Santafé (University of the Basque Country), Aritz Pérez (Universidad Politécnica de Madrid), Vı́ctor Robles (University of the Basque Country)
Résumé : 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.