The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks

Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook anal...

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Vydáno v:Frontiers in physiology Ročník 9; s. 680 - 13
Hlavní autoři: Naldi, Aurélien, Hernandez, Céline, Levy, Nicolas, Stoll, Gautier, Monteiro, Pedro T., Chaouiya, Claudine, Helikar, Tomáš, Zinovyev, Andrei, Calzone, Laurence, Cohen-Boulakia, Sarah, Thieffry, Denis, Paulevé, Loïc
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland Frontiers 19.06.2018
Frontiers Media S.A
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ISSN:1664-042X, 1664-042X
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Abstract Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve. The CoLoMoTo Interactive Notebook provides a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks. This framework combines the power of different technologies to ensure repeatability and to reduce users' learning curve of these technologies. The framework is distributed as a Docker image with the tools ready to be run without any installation step besides Docker, and is available on Linux, macOS, and Microsoft Windows. The embedded computational workflows are edited with a Jupyter web interface, enabling the inclusion of textual annotations, along with the explicit code to execute, as well as the visualization of the results. The resulting notebook files can then be shared and re-executed in the same environment. To date, the CoLoMoTo Interactive Notebook provides access to the software tools GINsim, BioLQM, Pint, MaBoSS, and Cell Collective, for the modeling and analysis of Boolean and multi-valued networks. More tools will be included in the future. We developed a Python interface for each of these tools to offer a seamless integration in the Jupyter web interface and ease the chaining of complementary analyses.
AbstractList Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve. The CoLoMoTo Interactive Notebook provides a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks. This framework combines the power of different technologies to ensure repeatability and to reduce users' learning curve of these technologies. The framework is distributed as a Docker image with the tools ready to be run without any installation step besides Docker, and is available on Linux, macOS, and Microsoft Windows. The embedded computational workflows are edited with a Jupyter web interface, enabling the inclusion of textual annotations, along with the explicit code to execute, as well as the visualization of the results. The resulting notebook files can then be shared and re-executed in the same environment. To date, the CoLoMoTo Interactive Notebook provides access to the software tools GINsim, BioLQM, Pint, MaBoSS, and Cell Collective, for the modeling and analysis of Boolean and multi-valued networks. More tools will be included in the future. We developed a Python interface for each of these tools to offer a seamless integration in the Jupyter web interface and ease the chaining of complementary analyses.
Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve. The CoLoMoTo Interactive Notebook provides a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks. This framework combines the power of different technologies to ensure repeatability and to reduce users' learning curve of these technologies. The framework is distributed as a Docker image with the tools ready to be run without any installation step besides Docker, and is available on Linux, macOS, and Microsoft Windows. The embedded computational workflows are edited with a Jupyter web interface, enabling the inclusion of textual annotations, along with the explicit code to execute, as well as the visualization of the results. The resulting notebook files can then be shared and re-executed in the same environment. To date, the CoLoMoTo Interactive Notebook provides access to the software tools GINsim, BioLQM, Pint, MaBoSS, and Cell Collective, for the modeling and analysis of Boolean and multi-valued networks. More tools will be included in the future. We developed a Python interface for each of these tools to offer a seamless integration in the Jupyter web interface and ease the chaining of complementary analyses.Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve. The CoLoMoTo Interactive Notebook provides a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks. This framework combines the power of different technologies to ensure repeatability and to reduce users' learning curve of these technologies. The framework is distributed as a Docker image with the tools ready to be run without any installation step besides Docker, and is available on Linux, macOS, and Microsoft Windows. The embedded computational workflows are edited with a Jupyter web interface, enabling the inclusion of textual annotations, along with the explicit code to execute, as well as the visualization of the results. The resulting notebook files can then be shared and re-executed in the same environment. To date, the CoLoMoTo Interactive Notebook provides access to the software tools GINsim, BioLQM, Pint, MaBoSS, and Cell Collective, for the modeling and analysis of Boolean and multi-valued networks. More tools will be included in the future. We developed a Python interface for each of these tools to offer a seamless integration in the Jupyter web interface and ease the chaining of complementary analyses.
Analysing models of biological networks typically relies on workflows in which different software tools with sensitive parameters are chained together, many times with additional manual steps. The accessibility and reproducibility of such workflows is challenging, as publications often overlook analysis details, and because some of these tools may be difficult to install, and/or have a steep learning curve. The CoLoMoTo Interactive Notebook provides a unified environment to edit, execute, share, and reproduce analyses of qualitative models of biological networks.This framework combines the power of different technologies to ensure repeatability and to reduce users' learning curve of these technologies. The framework is distributed as a Docker image with the tools ready to be run without any installation step besides Docker, and is available on Linux, macOS, and Microsoft Windows. The embedded computational workflows are edited with a Jupyter web interface, enabling the inclusion of textual annotations, along with the explicit code to execute, as well as the visualisation of the results. The resulting notebook files can then be shared and re-executed in the same environment. To date, the CoLoMoTo Interactive Notebook provides access to software tools including GINsim, BioLQM, Pint, MaBoSS, and Cell Collective for the modelling and analysis of Boolean and multi-valued networks. More tools will be included in the future. We developed a Python interface for each of these tools to offer a seamless integration in the Jupyter web interface and ease the chaining of complementary analyses.
Author Hernandez, Céline
Zinovyev, Andrei
Helikar, Tomáš
Calzone, Laurence
Levy, Nicolas
Monteiro, Pedro T.
Chaouiya, Claudine
Cohen-Boulakia, Sarah
Thieffry, Denis
Naldi, Aurélien
Stoll, Gautier
Paulevé, Loïc
AuthorAffiliation 8 Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer , Villejuif , France
14 MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology , Paris , France
7 Université Pierre et Marie Curie , Paris , France
11 Department of Biochemistry, University of Nebraska-Lincoln , Lincoln, NE , United States
3 École Normale Supérieure de Lyon , Lyon , France
12 Institut Curie, PSL Research University , Paris , France
9 INESC-ID/Instituto Superior Técnico, University of Lisbon , Lisbon , Portugal
6 Institut National de la Santé et de la Recherche Médicale, U1138 , Paris , France
15 Lobachevsky University , Nizhni Novgorod , Russia
4 Université Paris Descartes/Paris V, Sorbonne Paris Cité , Paris , France
2 Laboratoire de Recherche en Informatique UMR8623, Université Paris-Sud, Centre National de la Recherche Scientifique, Université Paris-Saclay , Orsay , France
5 Équipe 11 Labellisée Ligue Nationale Contre le Cancer, Centre de Recherche des Cordeliers , Paris , France
10 Instit
AuthorAffiliation_xml – name: 12 Institut Curie, PSL Research University , Paris , France
– name: 13 Institut National de la Santé et de la Recherche Médicale, U900 , Paris , France
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– name: 1 Computational Systems Biology Team, Institut de Biologie de I'Ecole Normale Supérieure, Centre National de la Recherche Scientifique UMR8197, Institut National de la Santé et de la Recherche Médicale U1024, École Normale Supérieure, PSL Université , Paris , France
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– name: 10 Instituto Gulbenkian de Ciência , Oeiras , Portugal
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Copyright © 2018 Naldi, Hernandez, Levy, Stoll, Monteiro, Chaouiya, Helikar, Zinovyev, Calzone, Cohen-Boulakia, Thieffry and Paulevé. 2018 Naldi, Hernandez, Levy, Stoll, Monteiro, Chaouiya, Helikar, Zinovyev, Calzone, Cohen-Boulakia, Thieffry and Paulevé
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Keywords computational systems biology
model analysis
Python programming language
reproducibility
Boolean networks
Language English
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Reviewed by: Oksana Sorokina, University of Edinburgh, United Kingdom; Kyle B. Gustafson, Naval Surface Warfare Center Carderock Division (NSWCCD), United States
This article was submitted to Systems Biology, a section of the journal Frontiers in Physiology
Edited by: Pierre De Meyts, de Duve Institute, Belgium
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SubjectTerms Bioinformatics
Boolean networks
computational systems biology
Computer Science
model analysis
Physiology
Python programming language
reproducibility
Title The CoLoMoTo Interactive Notebook: Accessible and Reproducible Computational Analyses for Qualitative Biological Networks
URI https://www.ncbi.nlm.nih.gov/pubmed/29971009
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