Randomized SMILES strings improve the quality of molecular generative models

Overview of attention for article published in Journal of Cheminformatics, November 2019

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In the top 5% of all research outputs scored by Altmetric
Among the highest-scoring outputs from this source (#27 of 862)
High Attention Score compared to outputs of the same age (95th percentile)
High Attention Score compared to outputs of the same age and source (99th percentile)

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blogs: 4 blogs

twitter: 23 tweeters

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So far, Altmetric has seen 24 tweets from 23 users, with an upper bound of 56,599 followers.

@rguha @i_wwwish Was thinking of this one, which was also gdb-13, not 14. https://t.co/gGoIt9VFcc

14 Sep 2022

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Some of the perversity of ML: in this paper, the authors managed to improve their model by training it on many duplicates of the original training set, but with the SMILES strings in a non-canonical order! https://t.co/RudtFk0NYC

28 Aug 2022

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RT @tonets: Randomized SMILES strings improve the quality of molecular generative models | Journal of Cheminformatics | Full Text https://t…

06 Jan 2020

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RT @tonets: Randomized SMILES strings improve the quality of molecular generative models | Journal of Cheminformatics | Full Text https://t…

06 Jan 2020

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