The official sources for the RDKit library
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Updated
Jun 9, 2024 - HTML
The official sources for the RDKit library
Knowledge-guided-Pre-training-of-Graph-Transformer: The primary aim of this project is to leverage knowledge-guided pre-training techniques for enhancing the performance of graph transformers in molecular property prediction and drug discovery.
Object-oriented Representation for Chemical Spaces
Plausibility checks for generated molecule poses.
An exploration of the state of the art in the application of data science to quantum chemistry.
Drug target discovery using LLM and Knowledge graphs
Molecular Processing Made Easy.
MolDrug is a python package for drug-oriented optimization on the chemical space
A Windows GUI software for performing machine learning (ML) tasks in chemistry.
Interaction Fingerprints for protein-ligand complexes and more
Select materials to output molecules similar to the target molecule with MCTS Solver and Genetic Programming.
Quant Chem python scripts using PSI4 and RdKit
chemical viewer
MolEnc: a molecular encoder using rdkit and OCaml.
Discovering telomerase inhibitors with machine learning.
pytoda - PaccMann PyTorch Dataset Classes. Read the docs: https://paccmann.github.io/paccmann_datasets/
Plugin to show molecule images on mouseover using RDKit and Altair
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