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Fluxomics Modeling from Tracer Data — EMU & COBRA Training | 13C MFA & Flux Maps

NTHRYS >> Services >> Academic Services >> Training Programs >> Bioinformatics Training >> Metabolomics, Lipidomics & Fluxomics >> Fluxomics Modeling from Tracer Data — EMU & COBRA Training | 13C MFA & Flux Maps

Fluxomics Modeling from Tracer Data — EMU & COBRA — Hands-on

Learn how to move from stable isotope labeling data to quantitative intracellular flux maps. This module focuses on the EMU framework, 13C metabolic flux analysis workflows, building reaction and atom mapping models, fitting fluxes to tracer data and interpreting flux distributions together with COBRA-style constraint-based models for systems-level insight.

Fluxomics Modeling from Tracer Data — EMU & COBRA
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Session 1
Fee: Rs 8800
Fluxomics Concepts & EMU Framework
  • From tracer experiments to fluxomics questions
  • pool sizes vs fluxes steady state vs non steady state central carbon and beyond
  • EMU (Elementary Metabolite Unit) framework basics
  • isotopomers, isotopologues and EMUs atom transitions and mapping why EMUs scale better than full isotopomer models
  • Inputs, assumptions and data requirements
  • reaction network and reversibility measured labeling patterns and flux bounds identifiability and experimental design links
Session 2
Fee: Rs 11800
Building EMU / Isotopomer Models
  • Defining the metabolic network for 13C MFA
  • choosing reactions and compartments irreversible vs reversible splits linking to genome scale models
  • Atom mapping and EMU decomposition
  • carbon atom mapping for key reactions automatic vs manual EMU generation reducing model size without losing identifiability
  • Software workflows and file formats
  • model specification tables/spreadsheets exchange with COBRA style models export/import to flux analysis tools
Session 3
Fee: Rs 14800
Fitting Fluxes & Assessing Uncertainty
  • Objective functions and optimization strategies
  • least squares cost functions constraints and bounds on fluxes global vs local optimization approaches
  • Goodness of fit and residual diagnostics
  • chi square and residual plots detecting model misspecification sensitivity to individual measurements
  • Confidence intervals and identifiability analysis
  • profile likelihoods and confidence ranges flux coupling and unidentifiable directions using results to improve experimental design
Session 4
Fee: Rs 18800
Mini Capstone: Flux Map & Report
  • End to end 13C MFA on a teaching dataset
  • from labeling data to fitted fluxes
  • Visualizing and interpreting the flux map
  • graphical flux diagrams comparing conditions or genotypes linking fluxes to phenotypes and pathways
  • Deliverables: model files, flux tables & methods text
  • reaction and atom mapping specification flux estimates with confidence ranges ready to edit methods/results template


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