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@TheHashiramaSenju TheHashiramaSenju released this 06 Oct 07:34
· 11 commits to senju since this release
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AChE Molecular Machine Learning — v1.0.0

First formal research release of the AChE molecular machine-learning project.

This release contains the documented source code, experimental artifacts,
diagnostic outputs, forensic audit, and complete scientific report associated
with the current AChE pIC50 modelling workflow.

Included

  • ChEMBL AChE activity-data pipeline
  • Molecular curation and standardization
  • IC50 → pIC50 processing
  • Morgan fingerprints
  • RDKit molecular descriptors
  • Scaffold-aware evaluation
  • Random Forest
  • XGBoost
  • LightGBM
  • Optuna optimization
  • Grouped cross-validation
  • Held-out evaluation
  • Graph Neural Network evaluation
  • Diagnostic analyses
  • Forensic audit artifacts
  • Complete scientific report

Scientific note

This release is an evidence-bound research snapshot. The included forensic
audit documents methodological limitations identified during development,
including a unit-consistency issue concerning potency thresholding.

The release does not claim state-of-the-art performance or publication-ready
benchmark validity.

Citation

Please cite this software release using the repository's CITATION.cff.

A permanent archival DOI will be added after Zenodo deposition.

DOI: 10.5281/zenodo.23182018

Full Changelog: https://github.com/TheHashiramaSenju/AcHe-QSAR-modelling/commits/report

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