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Constructing and Analyzing Computational Models of Cell Signaling with BioModelAnalyzer.

Accepted version
Peer-reviewed

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Type

Article

Change log

Authors

Hall, Benjamin A 
Fisher, Jasmin 

Abstract

BioModelAnalyzer (BMA) is an open-source graphical tool for the development of executable models of protein and gene networks within cells. Based upon the Qualitative Networks formalism, the user can rapidly construct large networks, either manually or by connecting motifs selected from a built-in library. After the appropriate functions for each variable are defined, the user has access to three analysis engines to test the model. In addition to standard simulation tools, BMA includes an interface to the stability-testing algorithm and to a graphical Linear Temporal Logic (LTL) editor and analysis tool. Alongside this, we have developed a novel ChatBot to aid users constructing LTL queries and to explain the interface and run through tutorials. Here we present worked examples of model construction and testing via the interface. As an initial example, we discuss fate decisions in Dictyostelium discoidum and cAMP signaling. We go on to describe the workflow leading to the construction of a published model of the germline of C. elegans. Finally, we demonstrate how to construct simple models from the built-in network motif library. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Modeling the signaling network of Dictyostelium discoidum Basic Protocol 2: Modeling the germline progression of Caenorhabditis elegans Basic Protocol 3: Constructing a model of the cell cycle using motifs.

Description

Keywords

cell signaling, executable models, formal verification, systems biology, Cell Cycle, Cyclic AMP, Dictyostelium, Germ Cells, Models, Biological, Models, Molecular, Signal Transduction, Software

Journal Title

Curr Protoc Bioinformatics

Conference Name

Journal ISSN

1934-3396
1934-340X

Volume Title

69

Publisher

Wiley

Rights

All rights reserved
Sponsorship
Royal Society (Paul Instrument Fund) (UF130039)
MRC (unknown)
Medical Research Council (MC_UU_12022/9)
MRC (MR/N501876/1)
MRC
Medical Research Council (MR/S000216/1)
Royal Society (URF\R\191013)
Medical Research Council (MC_UU_12022/1)
MRC (MC_UU_12022/8)