Vincent Noël

TabularQual provides a spreadsheet-based format for annotating logical models, with tools to convert between spreadsheets and SBML-qual, enhancing model reuse and interoperability.

AstroLogics analyzes Boolean model ensembles to identify differences in dynamics and regulation through simulation-based clustering and visualization.

The paper introduces BoNesis, a tool for inferring Boolean networks from transcriptome data to model cellular differentiation and reprogramming, demonstrating its application in hematopoiesis and adipocyte/osteoblast differentiation.

This tutorial demonstrates how to use the CoLoMoTo software suite to perform reproducible dynamical analyses of logical models of biological networks.

This paper presents a community-driven benchmarking initiative for cell-based multiscale models, highlighting variations in tool implementations and advocating for standardized benchmarks and interoperability.

PhysiMeSS extends PhysiCell to model extracellular matrix fibers and their interactions, enabling more accurate simulations of cancer metastasis.

PhysiCell Studio is a graphical tool that simplifies the creation and editing of multicellular models by providing a user-friendly interface for XML-based model definition.

The paper introduces parallel implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators to handle increased model complexity.

PhysiBoSS 2.0 integrates stochastic Boolean and agent-based models for multiscale cancer simulations, improving modularity and functionality.

The paper develops a dynamic Boolean model to simulate psoriasis development and identifies potential drug targets by predicting interventions that mimic current treatments.

The paper presents a multiscale model of cancer cell invasion using PhysiBoSS, integrating spatial and intracellular processes to study migration modes and validate against experimental data.

The paper presents a computational framework for analyzing SARS-CoV-2-host interactions to identify drug targets and model disease mechanisms.

UPMaBoSS simulates cell population dynamics by extending MaBoSS to model interactions and death/division, revealing TNF-induced resistance mechanisms.

The paper develops personalized logical models to analyze cancer response to BRAF treatments, showing they correlate with experimental sensitivities using omics data without model training.

The paper provides an exact method to calculate stationary solutions and analyze parameter sensitivity in stochastic Boolean models without Monte Carlo simulations.