title: Integrating multiple types of data for signaling research: challenges and opportunities.
abstract: New technologies promise to provide unprecedented amounts of information that can build a foundation for creating predictive models of cell signaling pathways. To be useful, however, this information must be integrated into a coherent framework. In addition, the sheer volume of data gathered from the new technologies requires computational approaches for its analysis. Unfortunately, there are many barriers to data integration and analysis, mostly because of a lack of adequate data standards and their inconsistent use by scientists. However, solving the fundamental issues of data sharing will enable the investigation of entirely new areas of cell signaling research.
authors.affiliation: EMSL, Pacific Northwest National Laboratory, Richland, WA 99352, USA. steven.wiley@pnl.gov
authors.forename: H Steven
authors.initials: HS
authors.lastname: Wiley
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003628:Database Management Systems / Q000592:standards*; D023281:Genomics / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D040901:Proteomics / Q000592:standards / Q000706:statistics & numerical data; D012107:Research Design; D015398:Signal Transduction