AquaSol specifications
Information
| Unique identifier | OMICS_13722 |
|---|---|
| Name | AquaSol |
| Interface | Web user interface |
| Restrictions to use | None |
| Input data | Molecules described by undirected graphs representing their chemical structure, into feature vectors of fixed length |
| Input format | SMILES |
| Output data | Predicted solubility |
| Programming languages | Python |
| License | Apache License version 2.0 |
| Computer skills | Basic |
| Stability | Stable |
| Maintained | Yes |
Maintainer
- person_outline Pierre Baldi <>
Information
| Unique identifier | OMICS_13722 |
|---|---|
| Name | AquaSol |
| Software type | Package/Module |
| Interface | Command line interface |
| Restrictions to use | None |
| Input data | Molecules described by undirected graphs representing their chemical structure, into feature vectors of fixed length |
| Input format | SMILES |
| Output data | Predicted solubility |
| Operating system | Unix/Linux |
| Programming languages | Python |
| License | Apache License version 2.0 |
| Computer skills | Advanced |
| Stability | Stable |
| Maintained | Yes |
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Maintainer
- person_outline Pierre Baldi <>
AquaSol article
library_books
Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules.
2013 J Chem Inf Model
PMID: 23795551
DOI: 10.1021/ci400187y
AquaSol institution(s)
University College Dublin, School of Computer Science and Informatics, Dublin, Ireland; University of California, Irvine, Department of Computer Science, CA, USA
AquaSol 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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