Machine learning in bioinformatics.
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.
Larrañaga
Pedro
P
Intelligent Systems Group, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel de Lardizabal, 1, 20018 San Sebastian, Spain. pedro.larranaga@ehu.es
Calvo
Borja
B
Santana
Roberto
R
Bielza
Concha
C
Galdiano
Josu
J
Inza
Iñaki
I
Lozano
José A
JA
Armañanzas
Rubén
R
Santafé
Guzmán
G
Pérez
Aritz
A
Robles
Victor
V
D001185:Artificial Intelligence; D019295:Computational Biology; D023281:Genomics; D008962:Models, Theoretical; D040901:Proteomics