FastMM

FastMM accelerates constraint-based metabolic modeling for large-scale and personalized genome-wide analyses.

Key Features:

• Performance Efficiency: Achieves 2–400× speedups for flux balance and knockout analyses and ~8× speedup for MCMC sampling compared to COBRA 3.0 and other tools such as Cobrapy and Fast-SL.
• Supported Analyses: Implements flux balance analysis, single and double gene and metabolite knockout analyses, and Markov Chain Monte Carlo (MCMC) sampling.
• Consistency with COBRA 3.0: Produces outputs consistent with COBRA 3.0 while providing accelerated computation.
• Parallelization: Supports multiple threading parameters to accelerate high-throughput and large-scale computations.
• Computational Compatibility: Maintains computational compatibility with COBRA 3.0 workflows and formats.
• Implementation Language: Implemented via a rewritten C/C++ codebase derived from COBRA 3.0.

Scientific Applications:

• Metabolism-related disease mechanisms: Enables large-scale analyses to investigate metabolic alterations underlying disease mechanisms.
• Drug target prediction: Facilitates genome-scale prediction of metabolic drug targets via knockout and flux analyses.
• Biomarker identification: Supports identification of metabolic biomarkers for complex diseases through high-throughput modeling.
• Personalized metabolic profiling: Scales to personalized metabolic modeling, including individual cancer metabolic profiles from datasets such as the Cancer Genome Atlas (TCGA).

Methodology:

Built as a rewritten C/C++ codebase of COBRA 3.0 with optimizations to time-cost functions to accelerate constraint-based metabolic modeling computations.