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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/921199

Title
Integer programming models and algorithms for molecular classification of cancer from microarray data
Author/Creator
Berretta, Regina;  Mendes, Alexandre;  Moscato, Pablo
Description
Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciencesresearchers the opportunity to simultaneously measure thousands of gene expression levels under different conditions or coming from different cell lines. With appropriate data mining models and algorithms, this would lead to a systematic exploration of molecular classification of cancer, just one among many other exciting applications. The aim of this paper is to present a unified mathematical formalization for different feature selection problems and investigate their performance in classification of cancer cell-lines. We also present some results using the NCI60 dataset.
Relation
Twenty Eighth Australasian Computer Science Conference (ACSC 2005). Proceedings of the Twenty Eighth Australasian Computer Science Conference (ACSC 2005) (Newcastle, N.S.W. 31 January - 3 February, 2005) p. 361-370
Relation
http://crpit.com/abstracts/CRPITV38Berretta.html
Date
2005
Publisher
Australian Computer Society published in association with the ACM Digital Library
Keyword(s)
data mining;  feature selection;  combinatorial optimisation;  NCI60
Resource Type
conference paper
Identifier
http://hdl.handle.net/1959.13/921199
Identifier
ISBN:1920682201
Identifier
ISSN:1445-1336
Language
eng
Reviewed
Reviewed
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"Integer programming models and algorithms for molecular classification of cancer from microarray data"
 
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