Optimal selection of microarray analysis methods using a conceptual clustering algorithm

C. Rubio-Escudero, R. Romero-Záliz, O. Cordón, O. Harari, C. Del Val, I. Zwir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The rapid development of methods that select over/under expressed genes from microarray experiments have not yet matched the need for tools that identify informational profiles that differentiate between experimental conditions such as time, treatment and phenotype. Uncertainty arises when methods devoted to identify significantly expressed genes are evaluated: do all microarray analysis methods yield similar results from the same input dataset? do different microarray datasets require distinct analysis methods?. We performed a detailed evaluation of several microarray analysis methods, finding that none of these methods alone identifies all observable differential profiles, nor subsumes the results obtained by the other methods. Consequently, we propose a procedure that, given certain user-defined preferences, generates an optimal suite of statistical methods. These solutions are optimal in the sense that they constitute partial ordered subsets of all possible method-associations bounded by both, the most specific and the most sensitive available solution.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computing - EvoWorkshops 2006
Subtitle of host publicationEvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Proceedings
Pages172-183
Number of pages12
DOIs
StatePublished - Jul 14 2006
EventEvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC - Budapest, Hungary
Duration: Apr 10 2006Apr 12 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3907 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceEvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC
CountryHungary
CityBudapest
Period04/10/0604/12/06

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  • Cite this

    Rubio-Escudero, C., Romero-Záliz, R., Cordón, O., Harari, O., Del Val, C., & Zwir, I. (2006). Optimal selection of microarray analysis methods using a conceptual clustering algorithm. In Applications of Evolutionary Computing - EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC, Proceedings (pp. 172-183). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3907 LNCS). https://doi.org/10.1007/11732242_16