ReviewComputational and structural biotechnology journal2022
Attractor detection and enumeration algorithms for Boolean networks.
Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A Dataset of Benchmark Boolean Models for Gene Regulatory Networks.Scientific data · 2026Article
- A novel quantum algorithm for efficient attractor search in gene regulatory networks.Patterns (New York, N.Y.) · 2025Article
- Petri net on expanded networks computes the dynamics of finite multilevel models.Interface focus · 2025Article
- An open problem: Why are motif-avoidant attractors so rare in asynchronous Boolean networks?Journal of mathematical biology · 2025Article
- Mapping the attractor landscape of Boolean networks with biobalm.Bioinformatics (Oxford, England) · 2025Article
- Exploring the interplay between circadian rhythms and obesity: A Boolean network approach to understanding metabolic dysregulation.PloS one · 2025Article
- Characterizing behavioural differentiation in gene regulatory networks with representation graphs.NAR genomics and bioinformatics · 2024Article
- LogBTF: gene regulatory network inference using Boolean threshold network model from single-cell gene expression data.Bioinformatics (Oxford, England) · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
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Abstract
The Boolean network (BN) is a mathematical model used to represent various biological processes such as gene regulatory networks. The state of a BN is determined from the previous state and eventually reaches a stable state called an attractor. Due to its significance for elucidating the whole system, extensive studies have been conducted on analysis of attractors. However, the problem of detecting an attractor from a given BN has been shown to be NP-hard, and for general BNs, the time complexity of most existing algorithms is not guaranteed to be less than
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