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SMILES-18 dataset

Name: SMILES-18 dataset
Creator: Ignacio Pérez-Correa
Keywords: organic molecules, SMILES-encoding, cheminformatics, drug discovery

Research datakeyboard_double_arrow_right Dataset 27 May 2023Publisher:Zenodo

Authors: Ignacio Pérez-Correa;

doi: 10.5281/zenodo.7978076 , 10.5281/zenodo.7978077

SMILES-18 dataset

- Summary
- Subjects
- Metrics

Abstract

Dataset of organic molecules encoded as SMILES strings with 18,322,500 records collected from the Pubchem database. List of characters included in the dataset: Description SMILES Characters Atoms "C", "O", "N", "P", "S", "F", "Cl", "Br", "I", "Si", "B" Branches "(", ")" Rings "1", "2", "3", "4", "5", "6", "7", "8", "9" Bonds "=", "#" Ions "+", "-" Stereochemistry "/", "\" Miscellaneous "[", "]" For further information, please refer to the paper published on the Journal of Chemical Information and Modeling (https://doi.org/10.1021/acs.jcim.3c01548)

Keywords

organic molecules, SMILES-encoding, cheminformatics, drug discovery

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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