Complexity of fixed point counting problems in Boolean Networks
Florian Bridoux, Am\'elia Durbec, K\'evin Perrot, Adrien Richard

TL;DR
This paper investigates the computational complexity of determining fixed point counts in Boolean networks based on their influence digraphs, revealing a spectrum of complexity classes from P to NEXPTIME.
Contribution
It introduces a new perspective on fixed point problems in Boolean networks, classifying their complexity based on influence digraphs and fixed point counts.
Findings
Deciding if a SID can correspond to a BN with at least two fixed points is NP-complete.
Deciding if a SID can correspond to a BN with no fixed points is NEXPTIME-complete.
Complexity varies from P to NEXPTIME depending on fixed point constraints.
Abstract
A Boolean network (BN) with components is a discrete dynamical system described by the successive iterations of a function . 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 has a positive (resp. negative) influence on component meaning that tends to mimic (resp. negate) . 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 ). 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…
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