Computational models are essential in order to integrate and extract knowledge from the large amount of -omics data that are increasingly being collected thanks to high-throughput technologies. Unfortunately, the definition of an appropriate mathematical model is typically inaccessible to scientists with a poor computational background, whereas expert users often lack the proficiency required for biologically grounded models. Although many efforts have been put in software packages intended to bridge the gap between the two communities, once a model is defined, the problem of simulating and analyzing it within a reasonable time still persists. We here present COSYS, a web-based infrastructure for Systems Biology that guides the user through the definition, simulation and analysis of reaction-based models, including the deterministic and stochastic description of the temporal dynamics, and the Flux Balance Analysis. In the case of computationally demanding analyses, COSYS can exploit GPU-accelerated algorithms to speed up the computation, thereby making critical tasks, as for instance an exhaustive scan of parameter values, attainable to a large audience.

Cumbo, F., Nobile, M., Damiani, C., Colombo, R., Mauri, G., Cazzaniga, P. (2017). COSYS: A computational infrastructure for systems biology. In CIBB 2016 – 13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, Revised Selected Papers (pp.82-92). Springer Verlag [10.1007/978-3-319-67834-4_7].

COSYS: A computational infrastructure for systems biology

Nobile, MS;Damiani, C;Colombo, R;Mauri, G;Cazzaniga, P.
2017

Abstract

Computational models are essential in order to integrate and extract knowledge from the large amount of -omics data that are increasingly being collected thanks to high-throughput technologies. Unfortunately, the definition of an appropriate mathematical model is typically inaccessible to scientists with a poor computational background, whereas expert users often lack the proficiency required for biologically grounded models. Although many efforts have been put in software packages intended to bridge the gap between the two communities, once a model is defined, the problem of simulating and analyzing it within a reasonable time still persists. We here present COSYS, a web-based infrastructure for Systems Biology that guides the user through the definition, simulation and analysis of reaction-based models, including the deterministic and stochastic description of the temporal dynamics, and the Flux Balance Analysis. In the case of computationally demanding analyses, COSYS can exploit GPU-accelerated algorithms to speed up the computation, thereby making critical tasks, as for instance an exhaustive scan of parameter values, attainable to a large audience.
No
slide + paper
Flux balance analysis; GPGPU computing; High-performance computing; Modeling and simulation; Systems biology;
Flux balance analysis; GPGPU computing; High-performance computing; Modeling and simulation; Systems biology; Theoretical Computer Science; Computer Science (all)
English
13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2016
9783319678337
http://springerlink.com/content/0302-9743/copyright/2005/
Cumbo, F., Nobile, M., Damiani, C., Colombo, R., Mauri, G., Cazzaniga, P. (2017). COSYS: A computational infrastructure for systems biology. In CIBB 2016 – 13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, Revised Selected Papers (pp.82-92). Springer Verlag [10.1007/978-3-319-67834-4_7].
Cumbo, F; Nobile, M; Damiani, C; Colombo, R; Mauri, G; Cazzaniga, P
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/178453
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