title: Bioinformatic methods for integrating whole-genome expression results into cellular networks.
abstract: Extracting a comprehensive overview from the huge amount of information arising from whole-genome analyses is a significant challenge. This review critically surveys the state of the art methods that are used to connect information from functional genomic studies to biological function. Cluster analysis methods for inferring the correlation between genes are discussed, as are the methods for integrating gene expression information with existing information on biological pathways and the methods that combine cluster analysis with biological information to reconstruct novel biological networks.
authors.affiliation: Department of Pharmacology, University of Florence, Viale Pieraccini 6, 50139 Florence, Italy. duccio.cavalieri@unifi.it
authors.forename: Duccio
authors.initials: D
authors.lastname: Cavalieri
authors.forename: Carlotta
authors.initials: C
authors.lastname: De Filippo
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods / Q000458:organization & administration / Q000639:trends; D023281:Genomics / Q000379:methods / Q000458:organization & administration / Q000639:trends; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods