Identification of biological regulatory networks from Process Hitting models

Abstract

Qualitative formalisms offer a well-established alternative to the more traditionally used differential equation models of Biological Regulatory Networks (BRNs). These formalisms led to numerous theoretical works and practical tools to understand emerging behaviors. The analysis of the dynamics of very large models is however a rather hard problem, which led us to previously introduce the Process Hitting framework (PH), which is a particular class of nondeterministic asynchronous automata network (or safe Petri nets). Its major advantage lies in the efficiency of several static analyses recently designed to assess dynamical properties, making it possible to tackle very large models. In this paper, we address the formal identification of qualitative models of BRNs from PH models. First, the inference of the Interaction Graph from a PH model summarizes the signed influences between the components that are effective for the dynamics. Second, we provide the inference of all René Thomas models of BRNs that are compatible with a given PH. As the PH allows the specification of nondeterministic interactions between components, our inference emphasizes the ability of PH to deal with large BRNs with incomplete knowledge on interactions, where Thomas' approach fails because of the combinatorics of parameters. The inference of corresponding Thomas models is implemented using Answer Set Programming, which allows in particular an efficient enumeration of (possibly numerous) compatible parameterizations.

Inference of Delayed Biological Regulatory Networks from Time Series Data

“…Even if it already exists a few hybrid formalisms like time Petri Nets, hybrid automata, etc..., we propose this extension of the AN framework for several reasons. First, AN is a general framework that, although it was mainly used for biological networks [23,9], allows to represent any kind of dynamical models, and converters to several other representations are available. Indeed, a T-AN is a subclass of time Petri nets [10].…”

Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma

“…Nevertheless, there are advances in computer science that could solve the state space size problem. In particular, the methodology known as Process Hitting appears to be a viable solution to the problem, since it is capable of obtaining information from immensely large networks without being limited by the problem of the size of the state space ( Folschette et al, 2015 ; Sheikh et al, 2019 ). Although this technique is still being experimented, it is not ruled out as a viable solution in the medium-term ( Sheikh et al, 2019 ).…”

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“…We showed that our framework can encode them equivalently. In some cases, it is also possible to convert the obtained reduced automata network back to functional specification, for instance using [46].…”