pystablemotifs: Python library for attractor identification and control in Boolean networks
Abstract Summary pystablemotifs is a Python 3 library for analyzing Boolean networks. Its non-heuristic and exhaustive attractor identification algorithm was previously presented in Rozum et al. (2021). Here, we illustrate its performance improvements over similar methods and discuss how it uses out...
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Published in | Bioinformatics (Oxford, England) Vol. 38; no. 5; pp. 1465 - 1466 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
England
Oxford University Press
07.02.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Abstract
Summary
pystablemotifs is a Python 3 library for analyzing Boolean networks. Its non-heuristic and exhaustive attractor identification algorithm was previously presented in Rozum et al. (2021). Here, we illustrate its performance improvements over similar methods and discuss how it uses outputs of the attractor identification process to drive a system to one of its attractors from any initial state. We implement six attractor control algorithms, five of which are new in this work. By design, these algorithms can return different control strategies, allowing for synergistic use. We also give a brief overview of the other tools implemented in pystablemotifs.
Availability and implementation
The source code is on GitHub at https://github.com/jcrozum/pystablemotifs/.
Supplementary information
Supplementary data are available at Bioinformatics online. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1367-4803 1367-4811 |
DOI: | 10.1093/bioinformatics/btab825 |