Treffer: Executable biochemical space for specification and analysis of biochemical systems.

Title:
Executable biochemical space for specification and analysis of biochemical systems.
Authors:
Troják M; Systems Biology Laboratory, Masaryk University, Brno, Czech Republic., Šafránek D; Systems Biology Laboratory, Masaryk University, Brno, Czech Republic., Mertová L; Systems Biology Laboratory, Masaryk University, Brno, Czech Republic., Brim L; Systems Biology Laboratory, Masaryk University, Brno, Czech Republic.
Source:
PloS one [PLoS One] 2020 Sep 11; Vol. 15 (9), pp. e0238838. Date of Electronic Publication: 2020 Sep 11 (Print Publication: 2020).
Publication Type:
Journal Article; Research Support, Non-U.S. Gov't
Language:
English
Journal Info:
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Imprint Name(s):
Original Publication: San Francisco, CA : Public Library of Science
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Substance Nomenclature:
0 (Proteins)
Entry Date(s):
Date Created: 20200911 Date Completed: 20201102 Latest Revision: 20240329
Update Code:
20250114
PubMed Central ID:
PMC7485897
DOI:
10.1371/journal.pone.0238838
PMID:
32915842
Database:
MEDLINE

Weitere Informationen

Computational systems biology provides multiple formalisms for modelling of biochemical processes among which the rule-based approach is one of the most suitable. Its main advantage is a compact and precise mechanistic description of complex processes. However, state-of-the-art rule-based languages still suffer several shortcomings that limit their use in practice. In particular, the elementary (low-level) syntax and semantics of rule-based languages complicate model construction and maintenance for users outside computer science. On the other hand, mathematical models based on differential equations (ODEs) still make the most typical used modelling framework. In consequence, robust re-interpretation and integration of models are difficult, thus making the systems biology paradigm technically challenging. Though several high-level languages have been developed at the top of rule-based principles, none of them provides a satisfactory and complete solution for semi-automated description and annotation of heterogeneous biophysical processes integrated at the cellular level. We present the second generation of a rule-based language called Biochemical Space Language (BCSL) that combines the advantages of different approaches and thus makes an effort to overcome several problems of existing solutions. BCSL relies on the formal basis of the rule-based methodology while preserving user-friendly syntax of plain chemical equations. BCSL combines the following aspects: the level of abstraction that hides structural and quantitative details but yet gives a precise mechanistic view of systems dynamics; executable semantics allowing formal analysis and consistency checking at the level of the language; universality allowing the integration of different biochemical mechanisms; scalability and compactness of the specification; hierarchical specification and composability of chemical entities; and support for genome-scale annotation.

The authors have declared that no competing interests exist.