Formal Biochemical Space with Semantics in Kappa and BNGL

Děd, Tadeáš; Šafránek, David; Troják, Matej; Klement, Matej; Šalagovič, Jakub; Brim, Luboš

doi:10.1016/j.entcs.2016.09.017

Cited by 6 publications

(8 citation statements)

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“…We have presented the second generation of BCSL, a novel high-level language for the hierarchical description of biological structures and mechanistic description of chemical reactions by means of compact rules. With respect to the previous prototype [ 33 ] the framework fully utilises the specific view on the biochemical structures and reactions by means of direct semantics.…”

Section: Discussionmentioning

confidence: 99%

“…The latter issue gives the main motivation for making BCS a fully formal framework supporting executability and automated analysis. These points give the requirements we have attempted to address by introducing the Biochemical Space Language (BCSL) that combines the advantages of rule-based modelling with the simplicity of chemical reactions [33].…”

Section: Plos Onementioning

confidence: 99%

“…Moreover, we embed BCSL into the general context of the Comprehensive Modelling Platform. On the technical side, the definition of the language semantics is completely reformulated in terms of set theory in contrast to the infeasible process algebra approach originally employed in [33]. From the syntactic perspective, the key updates are the introduction of nesting operator, variables, and complex aliases.…”

Section: Plos Onementioning

confidence: 99%

“…The primary prototype of BCSL has been introduced in [33] with the formal semantics defined at the top of Kappa. However, BCSL aims at higher-level abstraction than Kappa that focuses on morphisms between protein binding sites.…”

Section: Plos Onementioning

confidence: 99%

“…means of compact rules. With respect to the previous prototype [33] the framework fully utilises the specific view on the biochemical structures and reactions by means of direct semantics.…”

Section: Plos Onementioning

confidence: 99%

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Executable biochemical space for specification and analysis of biochemical systems

et al. 2020

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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 rulebased 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.

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Section: Discussionmentioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

Section: Plos Onementioning

confidence: 99%

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