Galgo: a bi-objective evolutionary meta-heuristic identifies robust transcriptomic classifiers associated with patient outcome across multiple cancer types

Abstract Motivation Statistical and machine-learning analyses of tumor transcriptomic profiles offer a powerful resource to gain deeper understanding of tumor subtypes and disease prognosis. Currently, prognostic gene-expression signatures do not exist for all cancer types, and most developed to dat...

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Veröffentlicht in:	Bioinformatics 2020-12, Vol.36 (20), p.5037-5044
Hauptverfasser:	Guerrero-Gimenez, M E, Fernandez-Muñoz, J M, Lang, B J, Holton, K M, Ciocca, D R, Catania, C A, Zoppino, F C M
Format:	Artikel
Sprache:	eng
Schlagworte:	Breast Neoplasms Computational Biology Gene Expression Profiling Heuristics Humans Transcriptome
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