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Mendeley readers
Title |
Optimization and model reduction in the high dimensional parameter space of a budding yeast cell cycle model
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Published in |
BMC Systems Biology, June 2013
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DOI | 10.1186/1752-0509-7-53 |
Pubmed ID | |
Authors |
Cihan Oguz, Teeraphan Laomettachit, Katherine C Chen, Layne T Watson, William T Baumann, John J Tyson |
Abstract |
Parameter estimation from experimental data is critical for mathematical modeling of protein regulatory networks. For realistic networks with dozens of species and reactions, parameter estimation is an especially challenging task. In this study, we present an approach for parameter estimation that is effective in fitting a model of the budding yeast cell cycle (comprising 26 nonlinear ordinary differential equations containing 126 rate constants) to the experimentally observed phenotypes (viable or inviable) of 119 genetic strains carrying mutations of cell cycle genes. |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 5% |
United Kingdom | 2 | 3% |
Portugal | 1 | 2% |
Italy | 1 | 2% |
Malaysia | 1 | 2% |
Canada | 1 | 2% |
Netherlands | 1 | 2% |
Unknown | 49 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 18 | 31% |
Researcher | 12 | 20% |
Student > Master | 6 | 10% |
Student > Doctoral Student | 5 | 8% |
Student > Bachelor | 4 | 7% |
Other | 9 | 15% |
Unknown | 5 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 14 | 24% |
Biochemistry, Genetics and Molecular Biology | 8 | 14% |
Engineering | 8 | 14% |
Computer Science | 7 | 12% |
Mathematics | 3 | 5% |
Other | 10 | 17% |
Unknown | 9 | 15% |