Improving reproducibility of cheminformatics workflows with chembl-downloader

Fuente: arXiv
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Autore principale: Hoyt, Charles Tapley
Natura: Preprint
Pubblicazione: 2025
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author Hoyt, Charles Tapley
author_facet Hoyt, Charles Tapley
contents Many modern cheminformatics workflows derive datasets from ChEMBL, but few of these datasets are published with accompanying code for their generation. Consequently, their methodologies (e.g., selection, filtering, aggregation) are opaque, reproduction is difficult, and interpretation of results therefore lacks important context. Further, such static datasets quickly become out-of-date. For example, the current version of ChEMBL is v35 (as of December 2024), but ExCAPE-DB uses v20, Deep Confidence uses v23, the consensus dataset from Isigkeit _et al._ (2022) uses v28, and Papyrus uses v30. Therefore, there is a need for tools that provide reproducible bulk access to the latest (or a given) version of ChEMBL in order to enable researchers to make their derived datasets more transparent, updatable, and trustworthy. This article introduces `chembl-downloader`, a Python package for the reproducible acquisition, access, and manipulation of ChEMBL data through its FTP server. It can be downloaded under the MIT license from https://github.com/cthoyt/chembl-downloader and installed from PyPI with `pip install chembl-downloader.`
format Preprint
id arxiv_https___arxiv_org_abs_2507_17783
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Improving reproducibility of cheminformatics workflows with chembl-downloader
Hoyt, Charles Tapley
Quantitative Methods
Many modern cheminformatics workflows derive datasets from ChEMBL, but few of these datasets are published with accompanying code for their generation. Consequently, their methodologies (e.g., selection, filtering, aggregation) are opaque, reproduction is difficult, and interpretation of results therefore lacks important context. Further, such static datasets quickly become out-of-date. For example, the current version of ChEMBL is v35 (as of December 2024), but ExCAPE-DB uses v20, Deep Confidence uses v23, the consensus dataset from Isigkeit _et al._ (2022) uses v28, and Papyrus uses v30. Therefore, there is a need for tools that provide reproducible bulk access to the latest (or a given) version of ChEMBL in order to enable researchers to make their derived datasets more transparent, updatable, and trustworthy. This article introduces `chembl-downloader`, a Python package for the reproducible acquisition, access, and manipulation of ChEMBL data through its FTP server. It can be downloaded under the MIT license from https://github.com/cthoyt/chembl-downloader and installed from PyPI with `pip install chembl-downloader.`
title Improving reproducibility of cheminformatics workflows with chembl-downloader
topic Quantitative Methods
url https://arxiv.org/abs/2507.17783