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COSYS: A Computational Infrastructure for Systems Biology

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Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2016)

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.

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Acknowledgments

This work has been supported by SYSBIO Centre of Systems Biology, through the MIUR grant SysBioNet—Italian Roadmap for ESFRI Research Infrastructures.

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Correspondence to Paolo Cazzaniga .

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Cumbo, F., Nobile, M.S., Damiani, C., Colombo, R., Mauri, G., Cazzaniga, P. (2017). COSYS: A Computational Infrastructure for Systems Biology. In: Bracciali, A., Caravagna, G., Gilbert, D., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2016. Lecture Notes in Computer Science(), vol 10477. Springer, Cham. https://doi.org/10.1007/978-3-319-67834-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-67834-4_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67833-7

  • Online ISBN: 978-3-319-67834-4

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