Patrice Ravel

An extension of Modular Response Analysis for global perturbations and robust connectivity inference of gene regulatory networks.

This paper extends Modular Response Analysis to account for global perturbations and improves robustness in inferring gene regulatory networks.

Testing and overcoming the limitations of Modular Response Analysis

The paper improves Modular Response Analysis by addressing noise sensitivity, enabling non-independent perturbations, and incorporating nonlinearity and prior knowledge.

Differential predictive value of resident memory CD8+T cell subpopulations in non-small-cell lung cancer patients treated by immunotherapy

The paper identifies two TRM subpopulations in NSCLC patients and shows that only DP TRM predicts response to PD-1 blockade immunotherapy.

Modular response analysis reformulated as a multilinear regression problem

The paper reformulates modular response analysis as a multilinear regression problem to improve stability and performance in inferring biological networks from perturbation data.

Application of Modular Response Analysis to Medium- to Large-Size Biological Systems

This paper applies and improves modular response analysis to infer gene regulatory networks in large biological systems with over 1,000 components.

aiMeRA: A generic modular response analysis R package and its application to estrogen and retinoic acid receptors crosstalk

The paper introduces aiMeRA, an R package for modular response analysis, and applies it to study estrogen and retinoic acid receptor crosstalk using genomic data.