n-yoshikawa / ob-fragment-generation
☆12Updated 5 years ago
Related projects: ⓘ
- ☆10Updated 3 years ago
- Shape-based alignment of molecules using 3D point-based representation☆18Updated 6 months ago
- Automated de novo design of drug-like molecular libraries based on deep learning multi-objective optimization☆13Updated 4 years ago
- Software tools for fragment-based drug discovery (FBDD)☆27Updated 4 years ago
- Modeling Tanimoto distributions for RDKit☆16Updated 4 years ago
- Code for paper "Human-in-the-Loop Assisted de Novo Molecular Design".☆22Updated last year
- Python API for Pharmer☆11Updated 5 years ago
- pains filter using rdktit☆11Updated 9 years ago
- SIEVE-Score: interaction energy-based virtual screening method based on random forest.☆14Updated last year
- AutoCorrelation of Pharmacophore Features☆15Updated last year
- ☆12Updated 8 months ago
- ☆11Updated this week
- These files are meant to accompany "What are our models really telling us? A practical tutorial on avoiding common mistakes when buildin…☆11Updated 11 years ago
- A generative model for molecular generation via multi-step chemical reactions☆11Updated last month
- 3D molecular fingerprints (E3FP) paper repo☆14Updated 3 years ago
- tools for building qsar models☆14Updated 5 years ago
- ☆22Updated 4 months ago
- ☆13Updated 2 years ago
- ☆12Updated 5 years ago
- Official code for the publication "HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder".☆17Updated last year
- Jupyter Notebook Tutorials for Creating Chemical Space Networks☆30Updated 8 months ago
- GUIDEMOL: a Python graphical user interface for molecular descriptors based on RDKit☆10Updated 7 months ago
- A deep reinforcement learning library for conformer generation.☆18Updated 5 months ago
- A versatile workflow for the generation of receptor-based pharmacophore models for virtual screening☆22Updated last year
- ☆9Updated 2 years ago
- Repository for the featurization of the NiCOlit reaction dataset and machine learning model training for yield prediction☆11Updated 2 years ago
- ACGCN: Graph Convolutional Networks for Activity Cliff Prediction Between Matched Molecular Pairs (Park et al., 2022)☆16Updated last year
- A validating SMILES parser, with support for incomplete SMILES☆22Updated 2 years ago
- ☆10Updated last year
- ProCare: A Point Cloud Registration Approach to Align Protein Cavities☆29Updated last year