“Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models-Reference-Cited by-同舟云学术

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

Published:2018 Issue:28 Volume:9 Page:6091-6098
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Schwaller Philippe¹²³^ORCID,Gaudin Théophile¹²³,Lányi Dávid¹²³,Bekas Costas¹²³,Laino Teodoro¹²³

Affiliation:

1. IBM Research

2. Zurich

3. Switzerland

Abstract

Using a text-based representation of molecules, chemical reactions are predicted with a neural machine translation model borrowed from language processing.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2018/SC/C8SC02339E

Reference41 articles.

1. Computer-Assisted Design of Complex Organic Syntheses

2. Computer-assisted mechanistic evaluation of organic reactions. 1. Overview

3. SOPHIA, a Knowledge Base-Guided Reaction Prediction System - Utilization of a Knowledge Base Derived from a Reaction Database

4. Further Development of a Reaction Generator in the SOPHIA System for Organic Reaction Prediction. Knowledge-Guided Addition of Suitable Atoms and/or Atomic Groups to Product Skeleton

5. Modelling Chemical Reasoning to Predict and Invent Reactions

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