Literature DB >> 23356010

A novel ensemble approach for multicategory classification of DNA microarray data using biological relevant gene sets.

Miguel Reboiro-Jato1, Daniel Glez-Peña, Fernando Díaz, Florentino Fdez-Riverola.   

Abstract

An important emerging medical application domain for microarray technology is clinical decision support in the form of diagnosis of diseases. For this task, several computational methods ranging from statistical alternatives to more complex hybrid systems have been previously proposed in the literature. In this work we study the utilisation of several ensemble alternatives for the task of classifying microarray data by using prior knowledge known to be biologically relevant to the target disease. The experimental results using different datasets and several gene sets show that the proposal is able to outperform previous approaches by introducing diversity as different gene sets.

Mesh:

Year:  2012        PMID: 23356010     DOI: 10.1504/ijdmb.2012.050267

Source DB:  PubMed          Journal:  Int J Data Min Bioinform        ISSN: 1748-5673            Impact factor:   0.667


  2 in total

1.  EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer.

Authors:  Leila Mirsadeghi; Reza Haji Hosseini; Ali Mohammad Banaei-Moghaddam; Kaveh Kavousi
Journal:  BMC Med Genomics       Date:  2021-05-07       Impact factor: 3.063

2.  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

  2 in total

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