In silico approaches to microarray-based disease classification and gene function discovery.

Francisco Azuaje

doi:10.1080/078538902320322565

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In silico approaches to microarray-based disease classification and gene function discovery.

Francisco Azuaje

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Abstract

The automated analysis of transcriptional profiling data promises a wealth of information that may be used to develop a more complete understanding of gene function and interactions. Moreover, it may improve the effectiveness of complex diagnostic tasks. This article discusses important data mining and management techniques to analyse genome-wide expression data. It reviews some of the major discovery goals, methods and applications in a number of biomedical domains. Finally, this paper highlights key problems that need to be approached by a new generation of computational solutions.

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Algorithms Cluster Analysis Databases, Genetic Gene Expression Profiling Humans Models, Genetic Neural Networks, Computer Oligonucleotide Array Sequence Analysis Journal Article

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Francisco Azuaje. 2002. In silico approaches to microarray-based disease classification and gene function discovery.. https://doi.org/10.1080/078538902320322565

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