AquaSol specifications
- Unique identifier:
- OMICS_13722
- Restrictions to use:
- None
- Input format:
- SMILES
- Programming languages:
- Python
- Computer skills:
- Basic
- Maintained:
- Yes
- Interface:
- Web user interface
- Input data:
- Molecules described by undirected graphs representing their chemical structure, into feature vectors of fixed length
- Output data:
- Predicted solubility
- License:
- Apache License version 2.0
- Stability:
- Stable
AquaSol specifications
- Unique identifier:
- OMICS_13722
- Interface:
- Command line interface
- Input data:
- Molecules described by undirected graphs representing their chemical structure, into feature vectors of fixed length
- Output data:
- Predicted solubility
- Programming languages:
- Python
- Computer skills:
- Advanced
- Maintained:
- Yes
- Software type:
- Package/Module
- Restrictions to use:
- None
- Input format:
- SMILES
- Operating system:
- Unix/Linux
- License:
- Apache License version 2.0
- Stability:
- Stable
versioning

No versioning.
AquaSol distribution
download
AquaSol support
Maintainer
- Pierre Baldi <>
- Pierre Baldi <>
forum

No open topic.
forum

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Credits

Publications
-
(Lusci et al., 2013)
Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.
J Chem Inf Model.
PMID: 23795551 DOI: 10.1021/ci400187y
Institution(s)
University College Dublin, School of Computer Science and Informatics, Dublin, Ireland; University of California, Irvine, Department of Computer Science, CA, USA
Funding source(s)
This work was partly funded by a GREP Ph.D. scholarship from the Irish Research Council for Science, Engineering and Technology, by the SFI grant 10/RFP/GEN2749 and by the following grants: NSF IIS-0513376, NIH LM010235, and NIH NLM T15 LM07443.
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