pystablemotifs: Python library for attractor identification and control in Boolean networks
Author(s) -
Jordan C. Rozum,
Dávid Deritei,
Kyu Hyong Park,
Jorge Gómez Tejeda Zañudo,
Réka Albert
Publication year - 2021
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btab825
Subject(s) - attractor , python (programming language) , computer science , identification (biology) , source code , heuristic , theoretical computer science , algorithm , software , data mining , programming language , artificial intelligence , mathematics , mathematical analysis , botany , biology
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom