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Retrosynthesis
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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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
RETRO SYNFLOW: Discrete Flow Matching for Accurate and Diverse Single-Step Retrosynthesis
DiffER: Categorical Diffusion for Chemical Retrosynthesis
LLM-Augmented Chemical Synthesis and Design Decision Programs
Leveraging Large Language Models for enzymatic reaction prediction and characterization
Enhancing Chemical Reaction and Retrosynthesis Prediction with Large Language Model and Dual-task Learning
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
NatureLM: Deciphering the Language of Nature for Scientific Discovery
Retro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning
Enhancing Retrosynthesis with Conformer: A Template-Free Method
Leveraging Large Language Models as Knowledge-Driven Agents for Reliable Retrosynthesis Planning
GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation
ASKCOS: an open source software suite for synthesis planning
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge
BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction
Directly Optimizing for Synthesizability in Generative Molecular Design using Retrosynthesis Models
Accelerating the inference of string generation-based chemical reaction models for industrial applications
Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets
MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
Retro-prob: Retrosynthetic Planning Based on a Probabilistic Model
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining
DirectMultiStep: Direct Route Generation for Multi-Step Retrosynthesis
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction Predictions
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
Retrosynthesis Prediction via Search in (Hyper) Graph
Retrosynthesis prediction enhanced by in-silico reaction data augmentation
T-Rex: Text-assisted Retrosynthesis Prediction
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction
Predictive Chemistry Augmented with Text Retrieval
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