bio-systems-biology-context-specific-models

Name: bio-systems-biology-context-specific-models
Availability: InStock
Author: dailycafi

Integrate gene expression with genome-scale metabolic models using GIMME, iMAT, or INIT.

7|Updated Apr 5, 2026

Search Tags:#init #gene expression #cobrapy #context-specific modeling #gimme #imat #genome-scale model

Ready to run

npx skills add https://github.com/dailycafi/metabolism-skills --skill bio-systems-biology-context-specific-models

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bio-systems-biology-context-specific-models
Source: https://github.com/dailycafi/metabolism-skills/tree/main/skills/systems-biology/context-specific-models
Command: npx skills add https://github.com/dailycafi/metabolism-skills --skill bio-systems-biology-context-specific-models

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Constrain generic genome-scale metabolic models (GEMs) with transcriptomics or proteomics to produce tissue-, cell-type-, or condition-specific metabolic networks that reflect active metabolism and enable context-aware flux predictions.

Core Features & Use Cases

Expression integration: Map gene or protein abundance to reactions using GPR rules and aggregate using max/min/mean logic.
Context model algorithms: Apply GIMME, iMAT, or INIT-style approaches to penalize low-expression reactions and enforce minimum biological objectives.
Validation & comparison: Preserve growth or objective activity, quantify constrained reactions, and compare flux distributions between original and context models.
Use Case: Create a liver-specific Recon3D model from GTEx TPMs to study altered pathway activity in metabolic disease or build cancer cell models from tumor RNA-seq.

Quick Start

Create a liver-specific metabolic model from Recon3D using GTEx TPMs and apply GIMME to constrain reactions based on expression.

Frequently Asked Questions about bio-systems-biology-context-specific-models

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a tissue-specific metabolic model from RNA-seq data?▼

Context-specific modeling constrains a genome-scale metabolic model by mapping gene or protein expression levels to reactions via GPR rules, penalizing low-expression pathways to reflect active metabolism in specific tissues or conditions.

Can I use COBRApy models for context-specific metabolic modeling?▼

Yes, context-specific modeling requires a COBRApy-compatible model, an optimization solver, and the Python scientific stack to perform thresholding and LP/MILP optimization for tasks like tissue modeling and cancer metabolism analysis.

What is the best way to create a cancer cell metabolic model from tumor RNA-seq?▼

Create a cancer cell metabolic model by mapping normalized tumor RNA-seq gene expression to a genome-scale model, then apply GIMME, iMAT, or INIT algorithms to enforce minimum biological objectives and constrain condition-specific flux distributions.

Do I need an optimization solver for GIMME and iMAT genome-scale modeling?▼

Yes, an optimization solver is required for GIMME and iMAT genome-scale modeling to perform LP/MILP optimization, map gene-to-expression levels, and accurately constrain reactions based on matched gene IDs within the Python scientific stack.

How does gene expression mapping work for context-specific metabolic reconstructions?▼

Gene expression mapping for context-specific reconstructions uses GPR rules to link gene or protein abundance to metabolic reactions, aggregating values using max, min, or mean logic to threshold and penalize inactive pathways in the model.

What are the limitations of context-specific modeling for single-cell reconstructions?▼

Limitations of context-specific modeling include the strict requirement for matching gene IDs between expression data and the genome-scale model, and the need to preserve growth objectives while validating constrained reactions in aggregated single-cell reconstructions.