Computing Molecular Signatures as Optima of a Bi-Objective Function: Method and Application to Prediction in Oncogenomics | Zendy

Vincent Gardeux | Zendy; Rachid Chelouah | Zendy; Maria Fernanda Barbosa Wanderley | Zendy; Patrick Siarry | Zendy; Antônio P. Braga | Zendy; Fabien Reyal | Zendy; Roman Rouzier | Zendy; Lajos Pusztai | Zendy; René Natowicz | Zendy

Open Access

Computing Molecular Signatures as Optima of a Bi-Objective Function: Method and Application to Prediction in Oncogenomics

Author(s) -

Vincent Gardeux,

Rachid Chelouah,

Maria Fernanda Barbosa Wanderley,

Patrick Siarry,

Antônio P. Braga,

Fabien Reyal,

Roman Rouzier,

Lajos Pusztai,

René Natowicz

Publication year - 2015

Publication title -

cancer informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.606

H-Index - 31

ISSN - 1176-9351

DOI - 10.4137/cin.s21111

Subject(s) - feature selection , computer science , pattern recognition (psychology) , classifier (uml) , data mining , cross validation , artificial intelligence , mathematics , machine learning

Filter feature selection methods compute molecular signatures by selecting subsets of genes in the ranking of a valuation function. The motivations of the valuation functions choice are almost always clearly stated, but those for selecting the genes according to their ranking are hardly ever explicit.

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