TAILIEUCHUNG - Báo cáo khoa học: Identification of small scale biochemical networks based on general type system perturbations

New technologies enable acquisition of large data-sets containing genomic, proteomic and metabolic information that describe the state of a cell. These data-sets call for systematic methods enabling relevant information about the inner workings of the cell to be extracted. One important issue at hand is the understanding of the functional interactions between genes, proteins and metabolites. | ềFEBS Journal Identification of small scale biochemical networks based on general type system perturbations Henning Schmidt1 Kwang-Hyun Cho2 3 and Elling W. Jacobsen1 1 Signals Sensors and Systems Royal institute of Technology - KTH Stockholm Sweden 2 College of Medicine SeoulNationalUniversity Chongno-gu Seoul Korea 3 Korea Bio-MAX Institute SeoulNationalUniversity Gwanak-gu Korea Keywords biochemical networks identification Jacobian time-series measurements Correspondence E. W. Jacobsen Department of Automatic Control Royal institute of Technology -KTH Osquldasvag 10 S-10044 Stockholm Sweden Fax 46 8790 7329 Tel 46 8790 7325 E-mail jacobsen@ . Cho College of Medicine Seoul National university Chongno-gu Seoul 110-799 Korea and Korea Bio-MAX Institute SeoulNationalUniversity Gwanak-gu Seoul 151-818 Korea Fax 82 2887 2692 Tel 82 2887 2650 E-mail ckh-sb@ Received 22 December 2004 accepted 8 February 2005 doi New technologies enable acquisition of large data-sets containing genomic proteomic and metabolic information that describe the state of a cell. These data-sets call for systematic methods enabling relevant information about the inner workings of the cell to be extracted. One important issue at hand is the understanding of the functional interactions between genes proteins and metabolites. We here present a method for identifying the dynamic interactions between biochemical components within the cell in the vicinity of a steady-state. Key features of the proposed method are that it can deal with data obtained under perturbations of any system parameter not only concentrations of specific components and that the direct effect of the perturbations does not need to be known. This is important as concentration perturbations are often difficult to perform in biochemical systems and the specific effects of general type perturbations are usually highly uncertain or unknown. The basis of the method is a linear .

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