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Message-passing neural networks for molecular property modelling. Evaluation should account for chemical-series overlap and the intended application domain.
گزارش اطلاعات نادرست یا ادعای مالکیت
Message-passing neural networks for molecular property modelling. Evaluation should account for chemical-series overlap and the intended application domain.
اطلاعات با مراجع رسمی تطبیق داده شده است؛ آزمایشگاهی نیست. منبع استناد · آخرین بازبینی: 14/09/2026, 18:31:56 UTC
Use this citation format when referencing Chemprop in scientific publications and benchmark papers.
@software{chemprop_2026,
title = {{Chemprop}},
author = {{Chemprop contributors}},
year = {2026},
url = {https://github.com/chemprop/chemprop},
note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}Live scientific citations queried from Europe PMC and PubMed for Chemprop.
Missing values mean the catalog has no recorded information. They do not mean a feature is absent.
No software–hardware integration has been verified for this entry yet. Explore documented research workflows.
Chemprop Scientific Architecture · Credit: Chemprop contributors · Open original ↗
Research and editorial use Source & attribution ↗ License ↗
ابزارهای مشابه در همین حوزه علمی.
Source-scoped research method · Confirm distribution and exact release
ADMET-AI — admet-property-prediction
Research / method authors
Research AI model / method · Research code or publication
Diffusion-based ligand molecule generation constrained by specified pocket and pharmacophore interactions
Sekijima Lab
Source-scoped research method · Confirm distribution and exact release
DiffSBDD — structure-conditioned-molecular-generation
Research / method authors
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مشاهده همه اخبار BioAI →Public code
قیمت‌ها بر اساس آخرین رصد رسمی مستند شده‌اند. برای اطلاع از شرایط جاری به وبگاه رسمی مراجعه فرمایید.
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