An ensemble method for gene discovery based on DNA microarray data.

Xia Li; Shaoqi Rao; Tianwen Zhang; Zheng Guo; Qingpu Zhang; Kathy L Moser; Eric J Topol

doi:10.1360/03yc0127

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An ensemble method for gene discovery based on DNA microarray data.

Xia Li·Shaoqi Rao·Tianwen Zhang·Zheng Guo·Qingpu Zhang·Kathy L Moser·Eric J Topol

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Abstract

The advent of DNA microarray technology has offered the promise of casting new insights onto deciphering secrets of life by monitoring activities of thousands of genes simultaneously. Current analyses of microarray data focus on precise classification of biological types, for example, tumor versus normal tissues. A further scientific challenging task is to extract disease-relevant genes from the bewildering amounts of raw data, which is one of the most critical themes in the post-genomic era, but it is generally ignored due to lack of an efficient approach. In this paper, we present a novel ensemble method for gene extraction that can be tailored to fulfill multiple biological tasks including (i) precise classification of biological types; (ii) disease gene mining; and (iii) target-driven gene networking. We also give a numerical application for (i) and (ii) using a public microarrary data set and set aside a separate paper to address (iii).

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Algorithms Computational Biology Databases as Topic Genomics Markov Chains Models, Genetic Models, Statistical Models, Theoretical Oligonucleotide Array Sequence Analysis Software Statistics as Topic Journal Article Research Support, Non-U.S. Gov't

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Xia Li, Shaoqi Rao, Tianwen Zhang, Zheng Guo, Qingpu Zhang, Kathy L Moser, Eric J Topol. 2004. An ensemble method for gene discovery based on DNA microarray data.. https://doi.org/10.1360/03yc0127

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