跳到正文
FunCoding

mfa-pipeline-orchestrator

Orchestrate the full metabolic flux analysis pipeline from model loading to phenotype prediction and publication figures. Triggers when the user provides an organism name, BIGG model ID, or custom reaction list and wants end-to-end metabolic modelling run automatically.

Star
14,635
分类
科研
许可证
MIT
最近提交
2026年8月19日

external/agents/Biology-Agent/skills/mfa-pipeline-orchestrator/SKILL.md

在 GitHub 上查看

MFA Pipeline Orchestrator

Overview

Coordinates all mfa-agent sub-agents in sequence, tracking progress via progress/ markdown files so any failed step can be resumed independently.

Full pipeline:

Model source (BIGG ID / custom reactions)
  → [model-builder]     models/<Model>.json  +  validation report
  → [fba-runner]        simulations/fba_fluxes.csv  +  scan_summary.json
  → [flux-analyzer]     analysis/essentiality.csv  +  phase_plane.png
  → [metabolic-pheno-analyzer]  output/figures/*.pdf  +  yield table

Workflow

Step 0: Parse User Request

Extract and record in progress/step0_inputs.md:

  • Model source (BIGG ID or custom)
  • Organism and condition (aerobic/anaerobic, carbon source, concentration)
  • Objective reaction (biomass or product)
  • Gene knockouts to apply
  • Analysis goals (essentiality, phase plane, yield optimisation, WT vs. mutant comparison)
  • Target product (if yield analysis requested)

Step 1: Invoke model-builder

Provide: model source, medium constraints, objective, knockouts. Wait for progress/step1_metabolic_model.md. Read: model file path, WT growth rate, model statistics.

Step 2: Invoke fba-runner

Provide: model path, simulation types requested (FBA, pFBA, FVA, knockout screen), carbon source sweep if requested. Wait for progress/step2_fba_simulation.md. Read: flux CSV paths, essential gene count, secretion fluxes.

Step 3: Invoke flux-analyzer

Provide: model path, FBA results, analysis goals (essentiality, phase plane, sampling), nutrient pair for phase plane. Wait for progress/step3_flux_analysis.md. Read: essential genes, phase plane optimum, engineering targets.

Step 4: Invoke metabolic-pheno-analyzer

Provide: model path, all previous results, target product, publication requirements. Wait for progress/step4_metabolic_phenotype.md. Read: max theoretical yield, figure paths.

Progress File Specification

progress/step1_metabolic_model.md

# Step 1: Metabolic Model
## Status: PASS / FAIL
## Model: <BIGG_ID>.json
## Reactions: N  Metabolites: M  Genes: G
## WT growth rate: X h⁻¹
## Validation: mass balance errors=0, dead-ends=N

progress/step2_fba_simulation.md

# Step 2: FBA Simulation
## Status: PASS / FAIL
## Runs: FBA, pFBA, FVA, knockout screen
## WT growth rate: X h⁻¹ (pFBA: Y h⁻¹)
## Essential genes: N
## Key secretion products: [ethanol: X mmol/gDW/h, ...]
## Files: simulations/fba_fluxes.csv, simulations/gene_essentiality.csv

progress/step3_flux_analysis.md

# Step 3: Flux Analysis
## Status: PASS / FAIL
## Essential gene count: N
## Phase plane optimum: glucose=X, O2=Y → growth=Z h⁻¹
## Top engineering targets: [gene1, gene2, gene3]
## Files: analysis/phase_plane.png, analysis/essentiality.csv

Key Conventions

  • Never re-run completed steps — check progress file status before invoking sub-agents
  • Maximum total sub-agent retries: 10 across all steps
  • All file paths relative to working directory
  • The orchestrator does not run FBA itself — all computation delegated to sub-agents

相似的 Skill

wiki-query

PApaperclipai/paperclip101k近 7 天新增 2,948 个 star

官方

clinical-case-report

NEnexu-io/open-design101k近 7 天新增 1,126 个 star

systematic-literature-review

BYbytedance/deer-flow84k近 7 天新增 368 个 star

academic-paper-review

BYbytedance/deer-flow84k近 7 天新增 368 个 star

directory-submissions

COcoreyhaines31/marketingskills54k近 7 天新增 958 个 star

academic-paper

IMImbad0202/academic-research-skills52k近 7 天新增 972 个 star