Evidence map›Paper›PMID 26380549›Full record

ArticleCancer informatics2015

CoGNaC: A Chaste Plugin for the Multiscale Simulation of Gene Regulatory Networks Driving the Spatial Dynamics of Tissues and Cancer.

Simone Rubinacci, Alex Graudenzi, Giulio Caravagna, Giancarlo Mauri, James Osborne, Joe Pitt-Francis, Marco Antoniotti

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Article in Cancer informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Simone RubinacciDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
Alex GraudenziDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
Giulio CaravagnaDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
Giancarlo MauriDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.
James OsborneSchool of Mathematics and Statistics, University of Melbourne, Australia.
Joe Pitt-FrancisDepartment of Computer Science, University of Oxford, Oxford, UK.
Marco AntoniottiDepartment of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a Chaste plugin for the generation and the simulation of Gene Regulatory Networks (GRNs) in multiscale models of multicellular systems. Chaste is a widely used and versatile computational framework for the multiscale modeling and simulation of multicellular biological systems. The plugin, named CoGNaC (Chaste and Gene Networks for Cancer), allows the linking of the regulatory dynamics to key properties of the cell cycle and of the differentiation process in populations of cells, which can subsequently be modeled using different spatial modeling scenarios. The approach of CoGNaC focuses on the emergent dynamical behavior of gene networks, in terms of gene activation patterns characterizing the different cellular phenotypes of real cells and, especially, on the overall robustness to perturbations and biological noise. The integration of this approach within Chaste's modular simulation framework provides a powerful tool to model multicellular systems, possibly allowing for the formulation of novel hypotheses on gene regulation, cell differentiation, and, in particular, cancer emergence and development. In order to demonstrate the usefulness of CoGNaC over a range of modeling paradigms, two example applications are presented. The first of these concerns the characterization of the gene activation patterns of human T-helper cells. The second example is a multiscale simulation of a simplified intestinal crypt, in which, given certain conditions, tumor cells can emerge and colonize the tissue.

Indexed as

attractorscancer developmentcell differentiationchastegene regulatory networksmultiscale modeling

Identifiers

PMID26380549
PMCPMC4559197

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.