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1. Verfasser: Daxlia
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Veröffentlicht: Zenodo 2026
Online-Zugang:https://doi.org/10.5281/zenodo.19984812
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author Daxlia
author_facet Daxlia
contents <h3>Release v1.0.0</h3> <p>First stable release of RéseauFlux.</p> <p><strong>What it does:</strong> ML pipeline to rank metabolic interventions (KO, OE, down) for succinate production in E. coli iJO1366.</p> <p><strong>Key results:</strong></p> <blockquote> <p>Best single: ATPS4rpp KO → 16.38 mmol/gDW/h Best double: ATPM KO + O2tex KO → 16.80 mmol/gDW/h GBR cross‑validation ρ = 0.557 Holdout ρ = 0.602</p> </blockquote> <h3>Includes:</h3> <blockquote> <p>Source code (metabolic_ml_pipeline.py) README, license</p> </blockquote> <p><strong>Run: <code>python metabolic_ml_pipeline.py</code></strong></p> <p><strong>Full Changelog</strong>: https://github.com/Daxlia/ReseauFlux/commits/v1.0.0</p>
format Recurso digital
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institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Daxlia/ReseauFlux: v1.0.0
Daxlia
<h3>Release v1.0.0</h3> <p>First stable release of RéseauFlux.</p> <p><strong>What it does:</strong> ML pipeline to rank metabolic interventions (KO, OE, down) for succinate production in E. coli iJO1366.</p> <p><strong>Key results:</strong></p> <blockquote> <p>Best single: ATPS4rpp KO → 16.38 mmol/gDW/h Best double: ATPM KO + O2tex KO → 16.80 mmol/gDW/h GBR cross‑validation ρ = 0.557 Holdout ρ = 0.602</p> </blockquote> <h3>Includes:</h3> <blockquote> <p>Source code (metabolic_ml_pipeline.py) README, license</p> </blockquote> <p><strong>Run: <code>python metabolic_ml_pipeline.py</code></strong></p> <p><strong>Full Changelog</strong>: https://github.com/Daxlia/ReseauFlux/commits/v1.0.0</p>
title Daxlia/ReseauFlux: v1.0.0
url https://doi.org/10.5281/zenodo.19984812