{
 "id": "maomlab/AqSolDB",
 "owner": "maomlab",
 "name": "AqSolDB",
 "downloads": 720,
 "likes": 0,
 "last_modified": "2025-08-01T20:04:25.000Z",
 "stated_licence": "mit",
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  {
   "id": "curated",
   "licence": null,
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 "tasks": [
  "tabular-regression"
 ],
 "citation": "TY  - JOUR\n  AU  - Sorkun, Murat Cihan\n  AU  - Khetan, Abhishek\n    AU  - Er, S√ºleyman\n    PY  - 2019\n    DA  - 2019/08/08\nTI  - AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds\nJO  - Scientific Data\nSP  - 143\nVL  - 6\nIS  - 1\nAB  - Water is a ubiquitous solvent in chemistry and life. \nIt is therefore no surprise that the aqueous solubility of compounds has a key role in various domains, \nincluding but not limited to drug discovery, paint, coating, and battery materials design. \nMeasurement and prediction of aqueous solubility is a complex and prevailing challenge in chemistry. \nFor the latter, different data-driven prediction models have recently been developed to augment the physics-based modeling approaches. \nTo construct accurate data-driven estimation models, it is essential that the underlying experimental calibration data used by these models is of high fidelity and quality.\nExisting solubility datasets show variance in the chemical space of compounds covered, measurement methods, experimental conditions, \nbut also in the non-standard representations, size, and accessibility of data. \nTo address this problem, we generated a new database of compounds, AqSolDB, by merging a total of nine different aqueous solubility datasets, \ncurating the merged data, standardizing and validating the compound representation formats, marking with reliability labels, and providing 2D descriptors of compounds as a Supplementary Resour",
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 "reason": "The checks could not identify a recognised licence ID for at least one declared source dataset.",
 "revision": "c95582978d7978519f123fe6eea2574b5fce3659",
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