title: Predicting biological networks from genomic data.
abstract: Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate to high-throughput experimental methods.
authors.affiliation: Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany.
authors.forename: Eoghan D
authors.initials: ED
authors.lastname: Harrington
authors.forename: Lars J
authors.initials: LJ
authors.lastname: Jensen
authors.forename: Peer
authors.initials: P
authors.lastname: Bork
mesh_terms: D019295:Computational Biology; D023281:Genomics; D010802:Phylogeny