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Retrosynthesis

Retrosynthetic analysis is a pivotal synthetic methodology in organic chemistry that employs a reverse-engineering approach, initiating from the target compound and retroactively tracing potential synthesis routes and precursor molecules. This technique proves instrumental in sculpting efficient synthetic strategies for intricate molecules, thus catalyzing the evolution and progression of novel pharmaceuticals and materials.

Papers

Showing 5175 of 110 papers

TitleStatusHype
BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction0
BioNavi-NP: Biosynthesis Navigator for Natural Products0
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning0
ChemiRise: a data-driven retrosynthesis engine0
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases0
Data Transfer Approaches to Improve Seq-to-Seq Retrosynthesis0
Deep Learning Methods for Small Molecule Drug Discovery: A Survey0
DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning0
Energy-based View of Retrosynthesis0
Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning0
Enhancing Retrosynthesis with Conformer: A Template-Free Method0
Generating Molecules via Chemical Reactions0
G-MATT: Single-step Retrosynthesis Prediction using Molecular Grammar Tree Transformer0
Human-in-the-loop for a Disconnection Aware Retrosynthesis0
Learning Graph Models for Template-Free Retrosynthesis0
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis0
Learning to Plan Chemical Syntheses0
LLM-Augmented Chemical Synthesis and Design Decision Programs0
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction0
Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction0
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning0
Molecular Graph Enhanced Transformer for Retrosynthesis Prediction0
Molecule-Edit Templates for Efficient and Accurate Retrosynthesis Prediction0
MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension0
NatureLM: Deciphering the Language of Nature for Scientific Discovery0
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