Inferring Biological Regulatory Networks from Process Hitting models
نویسندگان
چکیده
The Process Hitting (PH) is a recently introduced framework to model concurrent processes. It is notably suitable to model Biological Regulatory Networks (BRNs) with partial knowledge of cooperations by defining the most permissive dynamics. On the other hand, the qualitative modeling of BRNs has been widely addressed using René Thomas’ formalism. Given a PH model of a BRN, we first tackle the inference of the underlying Interaction Graph between components. Then the inference of corresponding Thomas’ models is provided by inferring some parameters and enumerating the compatible parametrizations.
منابع مشابه
Comparison of MLP NN Approach with PCA and ICA for Extraction of Hidden Regulatory Signals in Biological Networks
The biologists now face with the masses of high dimensional datasets generated from various high-throughput technologies, which are outputs of complex inter-connected biological networks at different levels driven by a number of hidden regulatory signals. So far, many computational and statistical methods such as PCA and ICA have been employed for computing low-dimensional or hidden represe...
متن کاملUsing a State-Space Model and Location Analysis to Infer Time-Delayed Regulatory Networks
Computational gene regulation models provide a means for scientists to draw biological inferences from time-course gene expression data. Based on the state-space approach, we developed a new modeling tool for inferring gene regulatory networks, called time-delayed Gene Regulatory Networks (tdGRNs). tdGRN takes time-delayed regulatory relationships into consideration when developing the model. I...
متن کاملModeling gene regulatory networks: Classical models, optimal perturbation for identification of network
Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption. On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications. This is not an unrealistic goal since genes which are regulated by gene regulatory ...
متن کاملIdentification of biological regulatory networks from Process Hitting models
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 Proce...
متن کاملStatistical Inference of Biologically-plausible Dynamic Regulatory Networks with Core-leaf Topology
Inferring regulatory networks from data is an important but challenging problem, and a number of formulations have been advanced, including Bayesian networks, Boolean switching networks, and linear networks. However, biological realism calls for an approach that incorporates a full combination of dynamics, nonlinearity, stochasticity, and known aspects of the underlying biological network topol...
متن کامل