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Journal of Computer and System Sciences
Article . 2022 . Peer-reviewed
License: Elsevier TDM
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https://dx.doi.org/10.48550/ar...
Article . 2020
License: CC BY
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Complexity of fixed point counting problems in Boolean networks

Authors: Florian Bridoux; Amélia Durbec; Kévin Perrot; Adrien Richard;

Complexity of fixed point counting problems in Boolean networks

Abstract

A Boolean network (BN) with $n$ components is a discrete dynamical system described by the successive iterations of a function $f:\{0,1\}^n \to \{0,1\}^n$. This model finds applications in biology, where fixed points play a central role. For example, in genetic regulations, they correspond to cell phenotypes. In this context, experiments reveal the existence of positive or negative influences among components: component $i$ has a positive (resp. negative) influence on component $j$ meaning that $j$ tends to mimic (resp. negate) $i$. The digraph of influences is called signed interaction digraph (SID), and one SID may correspond to a large number of BNs (which is, in average, doubly exponential according to $n$). The present work opens a new perspective on the well-established study of fixed points in BNs. When biologists discover the SID of a BN they do not know, they may ask: given that SID, can it correspond to a BN having at least/at most $k$ fixed points? Depending on the input, we prove that these problems are in $\textrm{P}$ or complete for $\textrm{NP}$, $\textrm{NP}^{\textrm{NP}}$, $\textrm{NP}^{\textrm{#P}}$ or $\textrm{NEXPTIME}$. In particular, we prove that it is $\textrm{NP}$-complete (resp. $\textrm{NEXPTIME}$-complete) to decide if a given SID can correspond to a BN having at least two fixed points (resp. no fixed point).

47 pages

Keywords

FOS: Computer and information sciences, Discrete Mathematics (cs.DM), interaction graph, Analysis of algorithms and problem complexity, fixed points, Molecular Networks (q-bio.MN), Symbolic dynamics, Combinatorics in computer science, Computational Complexity (cs.CC), Boolean networks, Computer Science - Computational Complexity, Graph theory (including graph drawing) in computer science, FOS: Biological sciences, FOS: Mathematics, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), Mathematics - Combinatorics, Quantitative Biology - Molecular Networks, Combinatorics (math.CO), complexity, Computer Science - Discrete Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Top 10%
Green
bronze