title: Integration of omics data: how well does it work for bacteria?
abstract: In the current omics era, innovative high-throughput technologies allow measuring temporal and conditional changes at various cellular levels. Although individual analysis of each of these omics data undoubtedly results into interesting findings, it is only by integrating them that gaining a global insight into cellular behaviour can be aimed at. A systems approach thus is predicated on data integration. However, because of the complexity of biological systems and the specificities of the data-generating technologies (noisiness, heterogeneity, etc.), integrating omics data in an attempt to reconstruct signalling networks is not trivial. Developing its methodologies constitutes a major research challenge. Besides for their intrinsic value towards health care, environment and industry, prokaryotes are ideal model systems to further develop these methods because of their lower regulatory complexity compared with eukaryotes, and the ease with which they can be manipulated. Several successful examples outlined in this review already show the potential of the systems approach for both fundamental and industrial applications, which would be time-consuming or impossible to develop solely through traditional reductionist approaches.
authors.affiliation: Centre of Microbial and Plant Genetics (CMPG) Katholieke Universiteit Leuven, Kasteelpark Arenberg 20, Belgium.
authors.forename: Sigrid C J
authors.initials: SC
authors.lastname: De Keersmaecker
authors.forename: Inge M V
authors.initials: IM
authors.lastname: Thijs
authors.forename: Jos
authors.initials: J
authors.lastname: Vanderleyden
authors.forename: Kathleen
authors.initials: K
authors.lastname: Marchal
mesh_terms: D001419:Bacteria / Q000235:genetics* / Q000378:metabolism*; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods* / Q000639:trends; D020543:Proteome / Q000235:genetics* / Q000378:metabolism; D040901:Proteomics / Q000639:trends
chemical_list: D020543:Proteome