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).
翻译:含有美元元件的布林网络( BN) 是一个离散的动态系统, 由函数的连续重覆 $f: @ @ 0, 1 ⁇ n{ @ to @ 0, 1 ⁇ n$。 此模型在生物学中找到应用, 固定点在其中扮演着中心角色 。 例如, 在基因调节中, 它们与细胞苯型相对应 。 在这方面, 实验揭示了各组成部分之间是否存在正或负影响 : 元件对元件具有正( 负) 影响, 这意味着 $( resp) 通常会模仿( resp) $。 影响区划称为签名的交互比重( SID), 其中一种SID可能相当于大量 BN( 平均是双倍指数, 按美元计算 。 ) 当前的工作为对固定点进行完善的研究开辟了新视角。 当生物学家发现他们不知道 BN 的 SID (如果 SID, 它与至少/tr$ $_r\\ r\ r= 美元, r=rr=r=r=r=r=r=r=r=r=r=r=r=r=r=r=x。 它们 ro) 可以。 当我们在固定点时, 可以证明这些输入是完整的输入问题。