Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction
出版年份 2022 全文链接
标题
Permutation Invariant Graph-to-Sequence Model for Template-Free Retrosynthesis and Reaction Prediction
作者
关键词
-
出版物
Journal of Chemical Information and Modeling
Volume 62, Issue 15, Pages 3503-3513
出版商
American Chemical Society (ACS)
发表日期
2022-07-27
DOI
10.1021/acs.jcim.2c00321
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Valid, Plausible, and Diverse Retrosynthesis Using Tied Two-Way Transformers with Latent Variables
- (2021) Eunji Kim et al. Journal of Chemical Information and Modeling
- Meta Learning for Low-Resource Molecular Optimization
- (2021) Jiahao Wang et al. Journal of Chemical Information and Modeling
- RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions
- (2021) Xiaorui Wang et al. CHEMICAL ENGINEERING JOURNAL
- Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits
- (2021) Mikołaj Sacha et al. Journal of Chemical Information and Modeling
- Molecular graph enhanced transformer for retrosynthesis prediction
- (2021) Kelong Mao et al. NEUROCOMPUTING
- Enhancing Retrosynthetic Reaction Prediction with Deep Learning using Multiscale Reaction Classification
- (2019) Javier L. Baylon et al. Journal of Chemical Information and Modeling
- RDChiral: An RDKit Wrapper for Handling Stereochemistry in Retrosynthetic Template Extraction and Application
- (2019) Connor W. Coley et al. Journal of Chemical Information and Modeling
- Analyzing Learned Molecular Representations for Property Prediction
- (2019) Kevin Yang et al. Journal of Chemical Information and Modeling
- Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
- (2019) Philippe Schwaller et al. ACS Central Science
- Predicting Retrosynthetic Reactions Using Self-Corrected Transformer Neural Networks
- (2019) Shuangjia Zheng et al. Journal of Chemical Information and Modeling
- “Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models
- (2018) Philippe Schwaller et al. Chemical Science
- Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models
- (2017) Bowen Liu et al. ACS Central Science
- Computer-Assisted Retrosynthesis Based on Molecular Similarity
- (2017) Connor W. Coley et al. ACS Central Science
- Computer-Assisted Synthetic Planning: The End of the Beginning
- (2016) Sara Szymkuć et al. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
- Extended-Connectivity Fingerprints
- (2010) David Rogers et al. Journal of Chemical Information and Modeling
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now