SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 110 papers

TitleStatusHype
Computer-Assisted Retrosynthesis Based on Molecular SimilarityCode0
Leveraging Large Language Models for enzymatic reaction prediction and characterizationCode0
RLSynC: Offline-Online Reinforcement Learning for Synthon CompletionCode0
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction PredictionsCode0
Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence AnalysisCode0
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion ModelsCode0
RetroComposer: Composing Templates for Template-Based Retrosynthesis PredictionCode0
Value-Added Chemical Discovery Using Reinforcement Learning—0
Accelerating the inference of string generation-based chemical reaction models for industrial applications—0
A Graph to Graphs Framework for Retrosynthesis Prediction—0
ASKCOS: an open source software suite for synthesis planning—0
Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models—0
A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges—0
Automatic Retrosynthetic Pathway Planning Using Template-free Models—0
BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction—0
BioNavi-NP: Biosynthesis Navigator for Natural Products—0
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning—0
ChemiRise: a data-driven retrosynthesis engine—0
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases—0
Data Transfer Approaches to Improve Seq-to-Seq Retrosynthesis—0
Deep Learning Methods for Small Molecule Drug Discovery: A Survey—0
DeepRetro: Retrosynthetic Pathway Discovery using Iterative LLM Reasoning—0
Energy-based View of Retrosynthesis—0
Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning—0
Enhancing Retrosynthesis with Conformer: A Template-Free Method—0
Generating Molecules via Chemical Reactions—0
G-MATT: Single-step Retrosynthesis Prediction using Molecular Grammar Tree Transformer—0
Human-in-the-loop for a Disconnection Aware Retrosynthesis—0
Learning Graph Models for Template-Free Retrosynthesis—0
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis—0
Learning to Plan Chemical Syntheses—0
LLM-Augmented Chemical Synthesis and Design Decision Programs—0
MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction—0
Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction—0
Models Matter: The Impact of Single-Step Retrosynthesis on Synthesis Planning—0
Molecular Graph Enhanced Transformer for Retrosynthesis Prediction—0
Molecule-Edit Templates for Efficient and Accurate Retrosynthesis Prediction—0
MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension—0
NatureLM: Deciphering the Language of Nature for Scientific Discovery—0
PolyRetro: Few-shot Polymer Retrosynthesis via Domain Adaptation—0
Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy—0
Quantum Machine Learning for Material Synthesis and Hardware Security—0
RCsearcher: Reaction Center Identification in Retrosynthesis via Deep Q-Learning—0
Recent advances in artificial intelligence for retrosynthesis—0
RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning—0
RetroDiff: Retrosynthesis as Multi-stage Distribution Interpolation—0
RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design—0
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction—0
Retro-prob: Retrosynthetic Planning Based on a Probabilistic Model—0
Retro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning—0
Show:102550
← PrevPage 2 of 3Next →

No leaderboard results yet.