An Integrated In Silico Simulation and Biomatter Compilation Approach to Cellular Computation

Konur, Savas; Fellermann, Harold; Mierla, Larentiu Marian; Sanassy, Daven; Ladroue, Christophe; Kalvala, Sara; Gheorghe, Marian; Krasnogor, Natalio

doi:10.1007/978-3-319-33921-4_25

Cited by 4 publications

(3 citation statements)

References 44 publications

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“…Finally, in the context of synthetic biology, Konur et al in [56] illustrate the use of the Infobiotics Workbench [18], a modelling tool based on stochastic P systems, on some example of synthetic genetic Boolean gates. The authors based their tool on P systems, because this formalism allows the specification of sets of reactions in multiple compartments and transport of molecules among them.…”

Section: P Systemsmentioning

confidence: 99%

A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models

et al. 2020

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Gene Regulatory Networks (GRNs) represent the interactions among genes regulating the activation of specific cell functionalities, such as reception of (chemical) signals or reaction to environmental changes. Studying and understanding these processes is crucial: they are the fundamental mechanism at the basis of cell functioning, and many diseases are based on perturbations or malfunctioning of some gene regulation activities. In this paper, we provide an overview on computational approaches to GRN modelling and analysis. We start from the biological and quantitative modelling background notions, recalling differential equations and the Gillespie’s algorithm. Then, we describe more in depth qualitative approaches such as Boolean networks and some computer science formalisms, including Petri nets, P systems and reaction systems. Our aim is to introduce the reader to the problem of GRN modelling and to guide her/him along the path that goes from classical quantitative methods, through qualitative methods based on Boolean network, up to some of the most relevant qualitative computational methods to understand the advantages and limitations of the different approaches.

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Section: P Systemsmentioning

confidence: 99%

A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models

et al. 2020

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“…Several modeling tools have been developed to understand the dynamics of bacterial populations and the multicellular systems they form. − General cell population modeling tools include gro and CellModeller4, intended to simulate the biophysical patterning of multicellular systems in 2D, focusing on physical interactions and chemical signaling. BSim is another general tool which is used to model cells in 3D, providing a general agent-based platform in which the user can define custom rules to describe cellular behavior, as well as environmental structures via 3D meshes.…”

Section: Related Workmentioning

confidence: 99%

Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations

et al. 2017

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Simbiotics is a spatially explicit multiscale modeling platform for the design, simulation and analysis of bacterial populations. Systems ranging from planktonic cells and colonies, to biofilm formation and development may be modeled. Representation of biological systems in Simbiotics is flexible, and user-defined processes may be in a variety of forms depending on desired model abstraction. Simbiotics provides a library of modules such as cell geometries, physical force dynamics, genetic circuits, metabolic pathways, chemical diffusion and cell interactions. Model defined processes are integrated and scheduled for parallel multithread and multi-CPU execution. A virtual lab provides the modeler with analysis modules and some simulated lab equipment, enabling automation of sample interaction and data collection. An extendable and modular framework allows for the platform to be updated as novel models of bacteria are developed, coupled with an intuitive user interface to allow for model definitions with minimal programming experience. Simbiotics can integrate existing standards such as SBML, and process microscopy images to initialize the 3D spatial configuration of bacteria consortia. Two case studies, used to illustrate the platform flexibility, focus on the physical properties of the biosystems modeled. These pilot case studies demonstrate Simbiotics versatility in modeling and analysis of natural systems and as a CAD tool for synthetic biology.

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“…Due to its novel features to infer information about system behaviour, there is growing interest in applying this technique in systems biology [38,39]. Model checking has been applied to the analysis of various biological systems such as ERK/MAPK or FGF signalling pathway [40][41][42], EGFR pathway [43,44], T-cell receptor signalling pathway [45][46][47][48], cell cycle in eukaryotes [49,50], cell cycle control [51][52][53][54][55], mammalian cell cycle regulation [56,57], apoptosis network [58,59], bladder tumorigenesis [60], quorum sensing [61][62][63], biological control mechanisms [64], DNA computing [65][66][67], genetic oscillator [68,69], genetic Boolean gates [61,[70][71][72][73] and switches [73][74][75].…”

Section: Introductionmentioning

confidence: 99%

Verifiable biology

Konur

Gheorghe

Krasnogor

2023

J. R. Soc. Interface.

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The formalization of biological systems using computational modelling approaches as an alternative to mathematical-based methods has recently received much interest because computational models provide a deeper mechanistic understanding of biological systems. In particular, formal verification, complementary approach to standard computational techniques such as simulation, is used to validate the system correctness and obtain critical information about system behaviour. In this study, we survey the most frequently used computational modelling approaches and formal verification techniques for computational biology. We compare a number of verification tools and software suites used to analyse biological systems and biochemical networks, and to verify a wide range of biological properties. For users who have no expertise in formal verification, we present a novel methodology that allows them to easily apply formal verification techniques to analyse their biological or biochemical system of interest.

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An Integrated In Silico Simulation and Biomatter Compilation Approach to Cellular Computation

Cited by 4 publications

References 44 publications

A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models

A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models

Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations

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