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Integrative information management for systems biology

Swainston, Neil, Jameson, Daniel, Li, Peter, Spasic, Irena, Mendes, Pedro and Paton, Norman W. 2010. Integrative information management for systems biology. Lecture Notes in Computer Science 6254 , pp. 164-178. 10.1007/978-3-642-15120-0_13

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Systems biology develops mathematical models of biological systems that seek to explain, or better still predict, how the system behaves. In bottom-up systems biology, systematic quantitative experimentation is carried out to obtain the data required to parameterize models, which can then be analyzed and simulated. This paper describes an approach to integrated information management that supports bottom-up systems biology, with a view to automating, or at least minimizing the manual effort required during, creation of quantitative models from qualitative models and experimental data. Automating the process makes model construction more systematic, supports good practice at all stages in the pipeline, and allows timely integration of high throughput experimental results into models.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history > QH301 Biology
Uncontrolled Keywords: computational systems biology; Workflow
Additional Information: Data Integration in the Life Sciences: 7th International Conference, DILS 2010, Gothenburg, Sweden, August 25-27, 2010. Proceedings (ISBN: 9783642151194)
Publisher: Springer Verlag
ISBN: 3642151205
ISSN: 0302-9743
Last Modified: 04 Jun 2017 01:56

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