pystablemotifs: Python library for attractor identification and control in Boolean networks

Jordan C Rozum; Dávid Deritei; Kyu Hyong Park; Jorge Gómez Tejeda Zañudo; Réka Albert

doi:10.1093/bioinformatics/btab825

pystablemotifs: Python library for attractor identification and control in Boolean networks

Bioinformatics. 2022 Feb 7;38(5):1465-1466. doi: 10.1093/bioinformatics/btab825.

Authors

Jordan C Rozum¹, Dávid Deritei^{2

3}, Kyu Hyong Park¹, Jorge Gómez Tejeda Zañudo^{4

5}, Réka Albert^{1

6}

Affiliations

¹ Department of Physics, The Pennsylvania State University, University Park, PA 16802, USA.
² Department of Molecular Biology, Semmelweis University, Budapest 1085, Hungary.
³ Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
⁴ Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
⁵ Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.
⁶ Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA.

PMID: 34875008
DOI: 10.1093/bioinformatics/btab825

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.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.
Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Gene Library
Software*