meilerlab / MolKGNNLinks
MolKGNN is a deep learning model for predicting biological activity or molecular properties. It features in 1. SE(3)-invariance 2. conformation-invariance 3. interpretability. MolKGNN uses a novel molecular convolution to leverage the similarity of molecular neighborhood and kernels. It shows superior results in realistic drug discovery dataset…
☆20Updated 2 years ago
Alternatives and similar repositories for MolKGNN
Users that are interested in MolKGNN are comparing it to the libraries listed below
Sorting:
- A simple molecule fragmentation method.☆37Updated last year
- Geometry Deep Learning for Drug Discovery and Life Science☆71Updated last year
- Code for "HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention"☆51Updated 2 years ago
- ☆92Updated 2 years ago
- Molecule Optimization via Fragment-based Generative Models☆42Updated 2 years ago
- Chemical representation learning paper in Digital Discovery☆61Updated last year
- pre-training BERT with molecular data☆48Updated 3 years ago
- Kinase–drug binding prediction with calibrated uncertainty quantification☆23Updated last year
- Recursion's molecular foundation model☆58Updated 3 months ago
- ☆21Updated 3 years ago
- 🔥 PyTorch implementation of GNINA scoring function for molecular docking☆70Updated 6 months ago
- An E(3) Equivariant Variational Autoencoder for Molecular Linker Design☆48Updated 2 years ago
- Graph neural networks for molecular machine learning. Implemented and compatible with TensorFlow and Keras.☆61Updated 3 weeks ago
- Few-shot machine learning for low-data drug discovery.☆20Updated 3 years ago
- Official implementation for ActFound (Nature Machine Intelligence): A bioactivity foundation model using pairwise meta-learning☆43Updated 10 months ago
- Official implementation of "Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug Design"☆66Updated 9 months ago
- ☆26Updated last year
- Sample-efficient Generative Molecular Design using Memory Manipulation☆60Updated 3 months ago
- Awesome De novo drugs design papers☆90Updated last year
- Atom-in-SMILES tokenizer for SMILES strings.☆40Updated last year
- ☆40Updated 2 years ago
- SELFormer: Molecular Representation Learning via SELFIES Language Models☆98Updated 9 months ago
- generative model for drug discovery☆64Updated 2 months ago
- Multi-Scale Representation Learning on Proteins (NeurIPS 2021)☆48Updated 2 years ago
- ☆52Updated 2 months ago
- Fast and accurate molecular docking with an AI pose scoring function☆41Updated last year
- pythonic interface to virtual screening software☆89Updated 2 weeks ago
- Utilities for working with SMILES based encodings of molecules for deep learning (PyTorch oriented)☆81Updated last year
- MiniMol is a 10M-parameters molecular fingerprinting model pre-trained on >3300 biological and quantum tasks☆24Updated 3 months ago
- Retrosynthetic Accessibility (RA) score learned from computer aided synthesis planning☆90Updated 4 years ago