title: Integrating 'omic' information: a bridge between genomics and systems biology.
abstract: The availability of genome sequences for several organisms, including humans, and the resulting first-approximation lists of genes, have allowed a transition from molecular biology to 'modular biology'. In modular biology, biological processes of interest, or modules, are studied as complex systems of functionally interacting macromolecules. Functional genomic and proteomic ('omic') approaches can be helpful to accelerate the identification of the genes and gene products involved in particular modules, and to describe the functional relationships between them. However, the data emerging from individual omic approaches should be viewed with caution because of the occurrence of false-negative and false-positive results and because single annotations are not sufficient for an understanding of gene function. To increase the reliability of gene function annotation, multiple independent datasets need to be integrated. Here, we review the recent development of strategies for such integration and we argue that these will be important for a systems approach to modular biology.
authors.affiliation: Dana-Farber Cancer Institute and Department of Genetics, Harvard Medical School, SM858, 44 Binney Street, Boston, MA 02115, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Ge
authors.forename: Albertha J M
authors.initials: AJ
authors.lastname: Walhout
authors.forename: Marc
authors.initials: M
authors.lastname: Vidal
mesh_terms: D019295:Computational Biology / Q000639:trends*; D030541:Databases, Genetic; D030562:Databases, Protein; D005544:Forecasting; D023281:Genomics / Q000379:methods / Q000639:trends*; D025941:Protein Interaction Mapping; D040901:Proteomics / Q000379:methods / Q000639:trends*; D018511:Systems Integration