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Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN

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Analysis of human metabolism by reducing the complexity of the genome-scale models using redHUMAN

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Reconstruction and analysis of genome-scale metabolic networks in single organisms and microbial communities

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Modeling metabolic and signaling pathways in cancer cells

Optimization methods and objective functions for analysis of metabolic network models

Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models

Large-scale kinetic metabolic models of Pseudomonas putida KT2440 for consistent design of metabolic engineering strategies

Enhanced flux prediction by integrating relative expression and relative metabolite abundance into thermodynamically consistent metabolic models

Systematic reduction of genome-scale models for the study of metabolic phenotypes of human cells

pyTFA and matTFA: a Python package and a Matlab toolbox for Thermodynamics-based Flux Analysis

Studying cancer cells phenotypes integrating omics data in human reduced genome-scale metabolic models.