M@CBETH: a microarray classification benchmarking tool | Zendy

Nathalie Pochet | Zendy; Frizo Janssens | Zendy; Frank De Smet | Zendy; Kathleen Marchal | Zendy; Johan A. K. Suykens | Zendy; Bart L. R. De Moor | Zendy

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M@CBETH: a microarray classification benchmarking tool

Author(s) -

Nathalie Pochet,

Frizo Janssens,

Frank De Smet,

Kathleen Marchal,

Johan A. K. Suykens,

Bart L. R. De Moor

Publication year - 2005

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bti495

Subject(s) - benchmarking , computer science , microarray analysis techniques , microarray , data mining , microarray databases , service (business) , class (philosophy) , machine learning , artificial intelligence , biology , biochemistry , gene expression , economy , marketing , economics , business , gene

Microarray classification can be useful to support clinical management decisions for individual patients in, for example, oncology. However, comparing classifiers and selecting the best for each microarray dataset can be a tedious and non-straightforward task. The M@CBETH (a MicroArray Classification BEnchmarking Tool on a Host server) web service offers the microarray community a simple tool for making optimal two-class predictions. M@CBETH aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset. The M@CBETH web service intends to introduce an optimal use of clinical microarray data classification.

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