Laurent Heirendt

COBREXA.jl is a Julia package for scalable constraint-based metabolic modeling, designed for high-performance computing environments and multi-organism community models.

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.

The paper introduces a framework to predict how changes in omics data affect metabolic functions in mammalian cells using curated metabolic tasks and genome-scale networks.

GigaSOM.jl provides a scalable solution for clustering and visualizing large cytometry datasets, achieving high performance with distributed computing.

The paper introduces a toolbox for modeling microbial interactions and communities using metagenomic data and extends the COBRA Toolbox.

The paper introduces the Virtual Metabolic Human database, which integrates human and gut microbiome metabolism with nutrition and disease data to support biomedical research.

The paper presents two gender-specific whole-body metabolism models, Harvey and Harvetta, that integrate physiological and omics data to predict metabolic processes and interactions across organs.

The paper uses personalized microbial community models to analyze bile acid metabolism in healthy and IBD individuals, revealing distinct metabolic potentials and strain contributions.