Pierre Salvy

Symbolic Kinetic Models in Python (SKiMpy): Intuitive modeling of large-scale biological kinetic models

The paper introduces SKiMpy, a Python package for efficiently building and analyzing large-scale kinetic models in biological systems.

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

This paper introduces REKINDLE, a deep learning framework that generates kinetic models of metabolic networks with dynamic properties, demonstrating its efficiency and versatility through three studies.

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

This paper develops yETFL, an extended ME-model for Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics, demonstrating its predictive ability for growth rate, essential genes, and overflow metabolism.

Emergence of diauxie as an optimal growth strategy under resource allocation constraints in cellular metabolism

The paper develops a computational model to simulate diauxie in E. coli, showing that proteome allocation and regulatory networks optimize growth under resource constraints.

ETFL: A formulation for flux balance models accounting for expression, thermodynamics, and resource allocation constraints

The paper introduces ETFL, a new metabolic model formulation that integrates expression, thermodynamics, and resource allocation constraints, showing improved accuracy over traditional FBA in simulating proteome-limited growth.