Integrating Petri Nets and Flux Balance Methods in Computational Biology Models : a Methodological and Computational Practice

• Autorzy: Pernice Simone , Follia Laura , Balbo Gianfranco , Milanesi Luciano , Sartini Giulia , Totis Niccoló , Lió Pietro , Merelli Ivan , Cordero Francesca , Beccuti Marco

Identyfikatory

DOI

10.3233/FI-2020-1888

• Języki publikacji: EN

Abstrakty

EN

Computational Biology is a fast-growing field that is enriched by different data-driven methodological approaches and by findings and applications in a broad range of biological areas. Fundamental to these approaches are the mathematical and computational models used to describe the different states at microscopic (for example a biochemical reaction), mesoscopic (the signalling effects at tissue level), and macroscopic levels (physiological and pathological effects) of biological processes. In this paper we address the problem of combining two powerful classes of methodologies: Flux Balance Analysis (FBA) methods which are now producing a revolution in biotechnology and medicine, and Petri Nets (PNs) which allow system generalisation and are central to various mathematical treatments, for example Ordinary Differential Equation (ODE) specification of the biosystem under study. While the former is limited to modelling metabolic networks, i.e. does not account for intermittent dynamical signalling events, the latter is hampered by the need for a large amount of metabolic data. A first result presented in this paper is the identification of three types of cross-talks between PNs and FBA methods and their dependencies on available data. We exemplify our insights with the analysis of a pancreatic cancer model. We discuss how our reasoning framework provides a biologically and mathematically grounded decision making setting for the integration of regulatory, signalling, and metabolic networks and greatly increases model interpretability and reusability. We discuss how the parameters of PN and FBA models can be tuned and combined together so to highlight the computational effort needed to perform this task. We conclude with speculations and suggestions on this new promising research direction.

Słowa kluczowe

EN

computational biology; Petri nets; flux balance analysis

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2020
• Tom: Vol. 171, nr 1-4
• Strony: 367--392
• Opis fizyczny: Bibliogr. 57 poz., rys., tab., wykr.

Twórcy

autor

Pernice Simone

• Department of Computer Science, University of Torino, Italy

autor

Follia Laura

• Department of Computer Science, University of Torino, Italy

autor

Balbo Gianfranco

• Department of Computer Science, University of Torino, Italy

autor

Milanesi Luciano

• Institute for Biomendical Technologies, National Research Council, Segrate (Milan), Italy

autor

Sartini Giulia

• Department of Life Sciences and Systems Biology, University of Torino, Italy

autor

Totis Niccoló

• Department of Life Sciences and Systems Biology, University of Torino, Italy

autor

Lió Pietro

• Computer Laboratory, University of Cambridge, GB

autor

Merelli Ivan

• Institute for Biomendical Technologies, National Research Council, Segrate (Milan), Italy

autor

Cordero Francesca

• Department of Computer Science, University of Torino, Italy

autor

Beccuti Marco

• Department of Computer Science, University of Torino, Italy

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).