title: In silico approaches to microarray-based disease classification and gene function discovery.
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.
authors.affiliation: Department of Computer Science, University of Dublin, Trinity College, Ireland. Francisco.Azuaje@cs.tcd.ie
authors.forename: Francisco
authors.initials: F
authors.lastname: Azuaje
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis