Literature DB >> 15890742

M@CBETH: a microarray classification benchmarking tool.

Nathalie L M M Pochet1, Frizo A L Janssens, Frank De Smet, Kathleen Marchal, Johan A K Suykens, Bart L R De Moor.   

Abstract

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.

Entities:  

Mesh:

Year:  2005        PMID: 15890742     DOI: 10.1093/bioinformatics/bti495

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  FiGS: a filter-based gene selection workbench for microarray data.

Authors:  Taeho Hwang; Choong-Hyun Sun; Taegyun Yun; Gwan-Su Yi
Journal:  BMC Bioinformatics       Date:  2010-01-26       Impact factor: 3.169

2.  Signature Evaluation Tool (SET): a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures.

Authors:  Chih-Hung Jen; Tsun-Po Yang; Chien-Yi Tung; Shu-Han Su; Chi-Hung Lin; Ming-Ta Hsu; Hsei-Wei Wang
Journal:  BMC Bioinformatics       Date:  2008-01-28       Impact factor: 3.169

3.  GeneSrF and varSelRF: a web-based tool and R package for gene selection and classification using random forest.

Authors:  Ramón Diaz-Uriarte
Journal:  BMC Bioinformatics       Date:  2007-09-03       Impact factor: 3.169

4.  geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

Authors:  Miguel Reboiro-Jato; Joel P Arrais; José Luis Oliveira; Florentino Fdez-Riverola
Journal:  BMC Bioinformatics       Date:  2014-01-30       Impact factor: 3.169

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.