Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation
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Updated
Jan 4, 2024 - Python
Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation
AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.
Plausibility checks for generated molecule poses.
Geometric Latent Diffusion Models for 3D Molecule Generation
Official Code Repository for the paper "Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations" (ICML 2022)
DrugAssist: A Large Language Model for Molecule Optimization
[ICLR 2022] Data-Efficient Graph Grammar Learning for Molecular Generation
Recurrent Neural Network using randomized SMILES strings to generate molecules
Structure-based Drug Design; Reinforcement Learning and Genetic Algorithm
Official repository for "Categorical Normalizing Flows via Continuous Transformations"
Pose checks for 3D Structure-based Drug Design methods
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
A reinforcement learning library for material and molecule optimization
Official Github for "Molecular generative model via retrosynthetically prepared chemical building block assembly" (Advanced Science)
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization (AAAI 21')
Molecular SMILE generation with recurrent neural networks
Code for the paper "Exploiting Pretrained Biochemical Language Models for Targeted Drug Design", to appear in Bioinformatics, Proceedings of ECCB2022.
Multiresolution Equivariant Graph Variational Autoencoder (MGVAE) https://arxiv.org/abs/2106.00967
CORE: Automatic Molecule Optimization using Copy & Refine Strategy (AAAI 2020)
[NeurIPS'23] Source code of "Data-Centric Learning from Unlabeled Graphs with Diffusion Model": A data-centric transfer learning framework with diffusion model on graphs.
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