Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions-Reference-Cited by-同舟云学术

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Scaffold‐Directed Face Selectivity Machine‐Learned from Vectors of Non‐covalent Interactions

Published:2021-06-09 Issue:28 Volume:133 Page:15358-15363
ISSN:0044-8249
Container-title:Angewandte Chemie
language:en
Short-container-title:Angew. Chem.

Author:

Moskal Martyna¹²,Beker Wiktor¹²,Szymkuć Sara¹²,Grzybowski Bartosz A.¹²³^ORCID

Affiliation:

1. Institute of Organic Chemistry Polish Academy of Sciences Ul. Kasprzaka 44/52 01-224 Warsaw Poland

2. Allchemy, Inc. Highland IN USA

3. IBS Center for Soft and Living Matter and Department of Chemistry UNIST 50, UNIST-gil, Eonyang-eup, Ulju-gun Ulsan South Korea

Funder

Defense Advanced Research Projects Agency

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ange.202101986

Reference72 articles.

1.

2. Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?

3. “Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models

4. Neural Networks for the Prediction of Organic Chemistry Reactions

5. Prediction of Organic Reaction Outcomes Using Machine Learning

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1. Is Organic Chemistry Really Growing Exponentially?;Angewandte Chemie International Edition;2021-11-09

2. Is Organic Chemistry Really Growing Exponentially?;Angewandte Chemie;2021-11-09

3. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning;Angewandte Chemie International Edition;2021-09-12

4. Towards Data‐Driven Design of Asymmetric Hydrogenation of Olefins: Database and Hierarchical Learning;Angewandte Chemie;2021-09-12

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