J 2023

Rule-based Modelling of Biological Systems Using Regulated Rewriting

TROJÁK, Matej, David ŠAFRÁNEK, Samuel PASTVA and Luboš BRIM

Basic information

Original name

Rule-based Modelling of Biological Systems Using Regulated Rewriting

Authors

TROJÁK, Matej (703 Slovakia, belonging to the institution), David ŠAFRÁNEK (203 Czech Republic, belonging to the institution), Samuel PASTVA (703 Slovakia, belonging to the institution) and Luboš BRIM (203 Czech Republic, belonging to the institution)

Edition

Biosystems, Elsevier, 2023, 0303-2647

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 1.600 in 2022

RIV identification code

RIV/00216224:14330/23:00134056

Organization unit

Faculty of Informatics

UT WoS

000933884300001

Keywords in English

systems biology; rule-based modelling; regulations; multiset rewriting

Tags

International impact, Reviewed
Změněno: 8/4/2024 10:08, RNDr. Pavel Šmerk, Ph.D.

Abstract

V originále

In systems biology, models play a crucial role in understanding studied systems. There are many modelling approaches, among which rewriting systems provide a framework for describing systems on a mechanistic level. Describing biochemical processes often requires incorporating knowledge on an abstract level to simplify the system description or substitute the missing details. For this purpose, we present regulation mechanisms, an extension of this formalism with additional controls on the rewriting process. We introduce several regulation mechanisms and apply them to a rule-based language, a notation suitable for modelling biological phenomena. Finally, we demonstrate the usage of such regulations on several case studies from the biochemical domain.

Links

GA22-10845S, research and development project
Name: Studium role polyhydroxyalkanoátů u bakterie Schlegelella thermodepolymerans – slibného bakteriálního kandidáta pro biotechnologie nové generace (Acronym: PHAST)
Investor: Czech Science Foundation, Unraveling the role of polyhydroxyalkanoates in Schlegelella thermodepolymerans – promising environmental bacterium for next generation biotechnology
MUNI/G/1771/2020, interní kód MU
Name: Computational reconstruction of mechanistic framework underlying receptor tyrosine kinase function in signal transduction (Acronym: FGFSIGMOD)
Investor: Masaryk University, INTERDISCIPLINARY - Interdisciplinary research projects