MICOMWeb

MICOMWeb performs microbial community metabolic modeling of the human gut using the MICOM Python package, enabling simulation of growth and metabolic exchange fluxes from real abundance data.

Key Features:

• Metabolic modeling without coding: Users can perform flux balance analysis-based metabolic modeling without prior Python knowledge.
• Diet customization: Supports predefined and user-defined diets to generate ad hoc metabolic models.
• Multi-sequencing input compatibility: Processes real abundance data from metagenomic shotgun or 16S amplicon sequencing.
• High-throughput simulation: Provides computational infrastructure for simulating growth and metabolic exchange fluxes at metagenome scale.
• In silico experiment execution: Enables functional hypothesis generation for subsequent experimental validation.

Scientific Applications:

• Human gut microbiome modeling: Generates in silico metagenome-scale metabolic models of microbial communities from the human gut.
• Growth prediction: Simulates microbial growth under specified dietary conditions.
• Metabolic exchange analysis: Computes metabolic exchange fluxes between community members and their environment.
• Hypothesis generation: Serves as a functional hypothesis generator for experimental validation using previously published data.

Methodology:

MICOMWeb uses flux balance analysis with the MICOM Python package to simulate growth and metabolic exchange fluxes from real abundance data derived from metagenomic shotgun or 16S amplicon sequencing, incorporating predefined or user-defined diets.