34 citations · 40 across the 3 of their papers we have counts for
6 papers
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks
Alex White, Matthieu Vignes
Biological networks are a very convenient modelling and visualisation tool to discover knowledge from modern high-throughput genomics and postgenomics data sets. Indeed, biological…
Gene regulatory networks: a primer in biological processes and statistical modelling
Olivia Angelin-Bonnet, Patrick J. Biggs, Matthieu Vignes
Modelling gene regulatory networks not only requires a thorough understanding of the biological system depicted but also the ability to accurately represent this system from a math…
Inferring large graphs using l1-penalized likelihood
Magali Champion, Victor Picheny, Matthieu Vignes
We address the issue of recovering the structure of large sparse directed acyclic graphs from noisy observations of the system. We propose a novel procedure based on a specific for…
Exact and approximate inference in graphical models: variable elimination and beyond
Nathalie Peyrard, Marie-Josée Cros, Simon de Givry +5
Probabilistic graphical models offer a powerful framework to account for the dependence structure between variables, which is represented as a graph. However, the dependence betwee…
Bridging physiological and evolutionary time scales in a gene regulatory network
Gwenaëlle Marchand, Vân Anh Huynh-Thu, Nolan Kane +9
Gene regulatory networks (GRN) govern phenotypic adaptations and reflect the trade-offs between physiological responses and evolutionary adaptation that act at different time scale…
Multi-Domain Sampling With Applications to Structural Inference of Bayesian Networks
Qing Zhou
When a posterior distribution has multiple modes, unconditional expectations, such as the posterior mean, may not offer informative summaries of the distribution. Motivated by this…