Abstract
A goal of systems biology is to develop an integrated picture of how the myriad components of a biological system work together to produce responses to environmental inputs. Achieving this goal requires (1) assembling a list of the component parts of a cellular regulatory system, and (2) understanding how the connections between these components enable information processing. To work toward these ends, a number of methods have matured in parallel. The compilation of a cellular parts list has been accelerated by the advent of omics technologies, which enable simultaneous characterization of a large collection of biomolecules. A particular type of omics technology that is useful for understanding protein-protein interaction networks is proteomics, which can give information about a number of dimensions of the state of the cell’s proteins: quantification of protein abundances within the cell, characterization of the posttranslational modification state of the proteome through phosphopeptide enrichment, and identification of protein-protein interactions through co-immunoprecipitation. Mathematical models can be useful in analyzing proteomic data.
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Chylek, L.A. (2019). Using Mechanistic Models for Analysis of Proteomic Data. In: Hlavacek, W. (eds) Modeling Biomolecular Site Dynamics. Methods in Molecular Biology, vol 1945. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9102-0_12
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DOI: https://doi.org/10.1007/978-1-4939-9102-0_12
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