PyBoolNet: a python package for the generation, analysis and visualization of boolean networks

Klarner, Hannes; Streck, Adam; Siebert, Heike

doi:10.1093/bioinformatics/btw682

Cited by 86 publications

(98 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The presence of multiple (disjoint) attractors can represent alternative cell fates (such as cell differentiation states), while cyclic attractors further represent periodic behaviours (such as cell cycle or circadian rhythms). The computation of attractors is addressed by different software tools, such as bioLQM [31], GINsim [32], Pint [36], BoolSim [19], BooleanNet [3], pyBoolNet [25], and…”

Section: Dynamical Analysismentioning

confidence: 99%

See 1 more Smart Citation

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

Naldi

Hernandez

Levy

et al. 2018

Preprint

View full text Add to dashboard Cite

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. Python programming languageRecently, the scientific community has been increasingly concerned about difficulties in reproducing already published results. In the context of preclinical studies, observed difficulties to reproduce important findings have raised controversy (see e.g. [7,15,40,43], and [8] for a review on this topic). Although not invalidating the findings, these observations have shaken the community. In 2016, a Nature survey pointed to the multi-factorial origin of this "reproducibility crisis" [4]. Factors related to computational analyses were highlighted, in particular the unavailability of code and methods, along with the technical expertise required to reproduce the computations.The scientific community is progressively addressing this problem. Prestigious conferences (such as two major conferences from the database community, namely, VLDB 1 and SIGMOD 2 ) and journals such as PNAS 3 , Biostatistics [38], Nature [41] and Science [54], to name only a few, now encourage or even require published results to be accompanied by all the information necessary to reproduce them. While the reproducibility challenges have first been observed in domains where deluge of data were quickly becoming available (e.g., Next Generation Sequencing data analyses), the problem is now present in many (if not all) communities where computational analyses and simulations are performed. In particular, the System Biology community is facing a pro...

show abstract

Section: Dynamical Analysismentioning

confidence: 99%

“…The notebook can be previewed and downloaded at https://nbviewer.jupyter.org/github/colomoto/ colomoto-docker/blob/2018-03-31/tutorials/Reproducibility%20-%20model%20checking.ipynb25 you may have to use pip3 instead of pip depending on your configuration26 If using Docker Toolbox, the command should be executed within the Docker Terminal…”

mentioning

confidence: 99%

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

Naldi

Hernandez

Levy

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…BioLQM proposes an adapted version of the method implemented in PyBoolNet [17,18] using the clingo ASP solver [13], and introduces a new alternative implementation based on decision diagrams.…”

Section: Identification Of Attractorsmentioning

confidence: 99%

bioLQM: a java library for the manipulation and conversion of Logical Qualitative Models of biological networks

Naldi

2018

Preprint

View full text Add to dashboard Cite

Here we introduce bioLQM, a new Java software toolkit for the conversion, modification, and analysis of Logical Qualitative Models of biological regulatory networks, aiming to foster the development of novel complementary tools by providing core modelling operations. Based on the definition of multi-valued logical models, it implements import and export facilities, notably for the recent SBML-qual exchange format, as well as for formats used by several popular tools, facilitating the design of workflows combining these tools. Model modifications enable the definition of various perturbations, as well as model reduction, easing the analysis of large models. Another modification enables the study of multi-valued models with tools limited to the Boolean case. Finally, bioLQM provides a framework for the development of novel analysis tools. The current version implements the usual updating modes for model simulation (notably synchronous, asynchronous, and random asynchronous), as well as some static analysis features for the identification of attractors. The bioLQM software can be integrated into analysis workflows through command line and scripting interfaces. As a Java library, it further provides core data structures to the GINsim and EpiLog interactive tools, which supply graphical interfaces and additional analysis methods for cellular and multi-cellular qualitative models.

show abstract

“…Pint also provides interfaces with exact model-checkers, such as NuSMV [5], ITS [16] and Mole [25], taking advantage of implemented static model reduction to enhance their tractability on large models. Usual explicit reachable state graph analysis are also available, although other tools dedicated to Boolean or multi-valued networks already provide them, e.g., [10,14,18].…”

Section: Introductionmentioning

confidence: 99%

Pint: A Static Analyzer for Transient Dynamics of Qualitative Networks with IPython Interface

Paulevé

2017

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. The software Pint is devoted to the scalable analysis of the traces of automata networks, which encompass Boolean and discrete networks. Pint implements formal approximations of transient reachabilityrelated properties, including mutation prediction and model reduction. Pint is distributed with command line tools, as well as a Python module pypint. The latter provides a seamless integration with the Jupyter IPython notebook web interface, which allows to easily save, reuse, reproduce, and share workflows of model analysis. Pint can address networks with hundreds to thousands interacting components, which are typically intractable with standard approaches.

show abstract

PyBoolNet: a python package for the generation, analysis and visualization of boolean networks

Abstract: hannes.klarner@fu-berlin.de.

Cited by 86 publications

References 15 publications

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

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

bioLQM: a java library for the manipulation and conversion of Logical Qualitative Models of biological networks

Pint: A Static Analyzer for Transient Dynamics of Qualitative Networks with IPython Interface

Contact Info

Product

Resources

About