Evidence map›Paper›PMID 38253903›Full record

ArticleBulletin of mathematical biology2024

A Kinetic Finite Volume Discretization of the Multidimensional PIDE Model for Gene Regulatory Networks.

Mihály A Vághy, Irene Otero-Muras, Manuel Pájaro, Gábor Szederkényi

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mihály A VághyFaculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/a, Budapest, 1083, Hungary. vaghy.mihaly.andras@itk.ppke.hu.ORCID 0000-0002-6280-2514
Irene Otero-MurasInstitute for Integrative Systems Biology, Spanish Council for Scientific Research, Carrer del Catedràtic Agustín Escardino Benlloch, 46980, Valencia, Spain.
Manuel PájaroDepartment of Mathematics, Escola Superior de Enxeñaría Informática, University of Vigo, Campus Ourense, 32004, Ourense, Spain.
Gábor SzederkényiFaculty of Information Technology and Bionics, Pázmány Péter Catholic University, Práter u. 50/a, Budapest, 1083, Hungary.

Funding

Innovációs és Technológiai Minisztérium 131545Innovációs és Technológiai Minisztérium ÚNKP-22-3-I-PPKE-72Ministerio de Ciencia e Innovación PID2021-127888NA-I00Xunta de Galicia ED431C 2022/47Xunta de Galicia ED431G 2019/01
6 · The paper itself

Abstract

In this paper, a finite volume discretization scheme for partial integro-differential equations (PIDEs) describing the temporal evolution of protein distribution in gene regulatory networks is proposed. It is shown that the obtained set of ODEs can be formally represented as a compartmental kinetic system with a strongly connected reaction graph. This allows the application of the theory of nonnegative and compartmental systems for the qualitative analysis of the approximating dynamics. In this framework, it is straightforward to show the existence, uniqueness and stability of equilibria. Moreover, the computation of the stationary probability distribution can be traced back to the solution of linear equations. The discretization scheme is presented for one and multiple dimensional models separately. Illustrative computational examples show the precision of the approach, and good agreement with previous results in the literature.

Indexed as

Gene Regulatory NetworksMathematical ConceptsKineticsModels, BiologicalProbabilityCompartmental systemsFinite volume methodsGene regulatory networksKinetic systemsNumerical methodsPartial integro-differential equations

Identifiers

PMID38253903
PMCPMC10803439

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