Pinning Controllability of Boolean Networks: Application to Large-Scale Genetic Networks

This paper focuses on making up for the drawback of recent results about pinning controllability of Boolean control networks (BCNs). First of all, a sufficient criterion is derived for the controllability of BCNs. Based on this criterion, to make an arbitrary BCN be controllable, an efficient method is developed to design the feasible pinning strategy which involves identifying pinning nodes and determining control form. Comparing with the traditional pinning approach of which time complexity is $O(2^{2n})$, the time complexity of this pinning method is reduced to $O(n2^{3\kappa}+(n+m)^2)$ with the number of state variables $n$, that of input variables $m$ and the largest in-degree among all nodes $\kappa$. Since a practical genetic network is always sparsely connected, $\kappa$ is far less than $n$ despite its size being large-scale. Finally, a T-cell receptor kinetics model with $37$ state nodes and $3$ input nodes is considered to demonstrate the application of obtained theoretical results

A novel pinning observability strategy for large-scale Boolean networks and its applications

Observability is of biological and engineering significance for the study of large-scale Boolean networks (BNs), while sensors are commonly impossible or high-cost to be inflicted on all SVs. Taking an unobservable large-scale BNs into account, it is crucial to design an operably effective control strategy under which the controlled system achieves observability. In this paper, a novel pinning control strategy is developed for an unobservable BN. It takes advantage of the network structure (NS) with respect to (w.r.t.) $n$ SVs rather than the traditionary algebraic state space representation w.r.t. $2^n$ states. The application of NS information dramatically reduces the time complexity from $O(2^{2n})$ to $O(n2^{3\omega}+n^3)$, where $\omega$ and $p$ are respectively the largest out-degree of vertices and the number of senors. Moreover, the new approach is of benefit to identify the pinning nodes and concisely compute the corresponding feedback form for every pinning nodes. With regard to simulation, the T-LGL survival network with 18 SVs and T-cell receptor kinetics with 37 SVs and 3 input variables are investigated to demonstrate the availability of our theoretical results

Distributed Pinning Control Design for Probabilistic Boolean Networks

This paper investigates the stabilization of probabilistic Boolean networks (PBNs) via a novel pinning control strategy based on network structure. In a PBN, each node needs to choose a Boolean function from candidate Boolean function set at each time instance with certain probability. Owing to the stochasticity, the uniform state feedback controllers, which is independent of switching signal, might be out of work. Thereby, a criterion is derived to determine that under what condition uniform controllers can be applied, otherwise non-uniform controllers need to be utilized. Accordingly, an algorithm is designed to find a series of state feedback pinning controllers, under which such a PBN is stabilized to a prespecified steady state. It is worth pointing out that the pinning control used in this paper only requires local in-neighbors' information, rather than global information. Hence, it is also termed as distributed pinning control and reduces the computational complexity to a large extent. Profiting from this, it provides a potential to deal with some large-scale networks. Finally, the mammalian cell-cycle encountering a mutated phenotype is described as a PBN, and presented to demonstrate the obtained results

On quotients of Boolean control networks

In this paper, we focus on the study of quotients of Boolean control networks (BCNs) with the motivation that they might serve as smaller models that still carry enough information about the original network. Given a BCN and an equivalence relation on the state set, we consider a labeled transition system that is generated by the BCN. The resulting quotient transition system then naturally captures the quotient dynamics of the BCN concerned. We therefore develop a method for constructing a Boolean system that behaves equivalently to the resulting quotient transition system. The use of the obtained quotient system for control design is discussed and we show that for BCNs, controller synthesis can be done by first designing a controller for a quotient and subsequently lifting it to the original model. We finally demonstrate the applicability of the proposed techniques on a biological example

A New Approach to Pinning Control of Boolean Networks

Boolean networks (BNs) are discrete-time systems where nodes are inter-connected (here we call such connection rule among nodes as network structure), and the dynamics of each gene node is determined by logical functions. In this paper, we propose a new approach on pinning control design for global stabilization of BNs based on BNs' network structure, named as network-structure-based distributed pinning control. By deleting the minimum number of edges, the network structure becomes acyclic. Then, an efficient distributed pinning control is designed to achieve global stabilization. Compared with existing literature, the design of pinning control is not based on the state transition matrix of BNs. Hence, the computational complexity in this paper is reduced from $O(2^n\times 2^n)$ to $O(2\times 2^K)$, where $n$ is the number of nodes and $K\leq n$ is the largest number of in-neighbors of nodes. In addition, without using state transition matrix, global state information is no longer needed, the design of pinning control is just based on neighbors' local information, which is easier to be implemented. The proposed method is well demonstrated by several biological networks with different sizes. The results are shown to be simple and concise, while the traditional pinning control can not be applied for BNs with such a large dimension

Disturbance Decoupling and Instantaneous Fault Detection in Boolean Control Networks

The literature available on disturbance decoupling (DD) of Boolean control network (BCN) is built on a restrictive notion of what constitutes as disturbance decoupling. The results available on necessary and sufficient conditions are of limited applicability because of their stringent requirements. This work tries to expand the notion of DD in BCN to incorporate a larger number of systems deemed unsuitable for DD. The methods available are further restrictive in the sense that system is forced to follow trajectory unaffected by the disturbances rather than decoupling disturbances while the system follows its natural course. Some sufficient conditions are provided under which the problem can be addressed. This work tries to establish the notion of disturbance decoupling via feedback control,analogous to the classical control theory. This approach though, is not limited to DD problems and can be extended to the general control problems of BCNs. Determination of observability, which is sufficient for the fault detection, is proven to be NP-hard for Boolean Control Network. Algorithms based on reconstructability, a necessary condition, of BCN turn out to be of exponential complexity in general.In such cases it makes sense to search for the availability of some special structure in BCN that could be utilized for fault detection with minimal computational efforts. An attempt is made to address this problem by introducing instantaneous fault detection (IFD) and providing necessary and sufficient conditions for the same. Later necessary and sufficient conditions are proposed for solving the problem of instantaneous fault detection along with disturbance decoupling using a single controller