TY - JOUR
T1 - The CoLoMoTo interactive notebook
T2 - Accessible and reproducible computational analyses for qualitative biological networks
AU - Naldi, Aurélien
AU - Hernandez, Céline
AU - Levy, Nicolas
AU - Stoll, Gautier
AU - Monteiro, Pedro T.
AU - Chaouiya, Claudine
AU - Helikar, Tomáš
AU - Zinovyev, Andrei
AU - Calzone, Laurence
AU - Cohen-Boulakia, Sarah
AU - Thieffry, Denis
AU - Paulevé, Loïc
N1 - Publisher Copyright:
© 2018 Naldi, Hernandez, Levy, Stoll, Monteiro, Chaouiya, Helikar, Zinovyev, Calzone, Cohen-Boulakia, Thieffry and Paulevé.
PY - 2018/6/19
Y1 - 2018/6/19
N2 - 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.
AB - 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.
KW - Boolean networks
KW - Computational systems biology
KW - Model analysis
KW - Python programming language
KW - Reproducibility
UR - http://www.scopus.com/inward/record.url?scp=85048681681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048681681&partnerID=8YFLogxK
U2 - 10.3389/fphys.2018.00680
DO - 10.3389/fphys.2018.00680
M3 - Article
C2 - 29971009
AN - SCOPUS:85048681681
SN - 1664-042X
VL - 9
JO - Frontiers in Physiology
JF - Frontiers in Physiology
IS - JUN
M1 - 680
ER -