Publications

@article{Gómez-Vela2011b,

title = {Pattern Recognition in Biological Time Series},

author = {F. Gómez-Vela and F. Martínez-Álvarez and C. D. Barranco and N. Díaz-Díaz and D. Rodríguez-Baena and J. Aguilar-Ruiz},

doi = {10.1007/978-3-642-25274-7_17},

isbn = {978-3-642-25274-7},

year  = {2011},

date = {2011-11-01},

journal = {Advances in Artificial Intelligence},

pages = {164-172},

abstract = {Knowledge extraction from gene expression data has been one of the main challenges in the bioinformatics field during the last few years. In this context, a particular kind of data, data retrieved in a temporal basis (also known as time series), provide information about the way a gene can be expressed during time. This work presents an exhaustive analysis of last proposals in this area, particularly focusing on those proposals using non--supervised machine learning techniques (i.e. clustering, biclustering and regulatory networks) to find relevant patterns in gene expression.},

keywords = {Biclustering, Clustering, Gene Network},

pubstate = {published},

tppubtype = {article}

}