Reverse Dependencies of rdkit

The following projects have a declared dependency on rdkit:

• synutility — Utility for reaction modeling using graph grammar
• t5chem — A Unified Deep Learning Model for Multi-task Reaction Predictions
• thegolem — Framework for Graph Optimization and Learning by Evolutionary Methods
• toff — toff is a python package to get topologies from the OpenFF initiative
• topsearch — A Python package for topographical analysis of machine learning models and physical systems
• torch-geometric — Graph Neural Network Library for PyTorch
• torch-pgn — Proximity Graph Networks: Predicting ligand affinity with Message Passing Neural Networks
• toxsmi — PyTorch implementation of toxicity prediction models from SMILES.
• trimnet — Your library description
• tsflow — Python package for searching transition states and generating reaction complexes
• twinbooster — Python package for TwinBooster: Synergising Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery
• uamc-spectrophore — Python implementation of the spectrophore descriptor
• ugropy — Get UNIFAC functional groups of PubChem compounds or SMILES representation.
• unidock-tools — A data processing tool for Uni-Dock input and output
• unimol-tools — unimol_tools is a Python package for property prediciton with Uni-Mol in molecule, materials and protein.
• unique-uncertainty — UNIQUE is a Python package for benchmarking uncertainty estimation and quantification methods for Machine Learning models predictions.
• useful-rdkit-utils — A collection of useful RDKit functions
• vectorGC — Implementation of the Vector-GC method and its regression framework
• vendi-score — A diversity metric for machine learning
• vgd-counterfactuals — Counterfactual explanations for GNNs based on the visual graph dataset format
• visChem — A tool for chemical space visualization and clustering.
• visual-graph-datasets — Datasets for the training of graph neural networks (GNNs) and subsequent visualization of attributional explanations of XAI methods
• visyn-core — Core repository for datavisyn applications.
• vsom — the code of virtual screening of organic materials
• vsutils — Utility for reaction modeling using graph grammar
• wandb — A CLI and library for interacting with the Weights & Biases API.
• wfl — no summary
• workbench — Workbench: A Dashboard and Python API for creating and deploying AWS SageMaker Model Pipelines
• wsppchem — Water Solubility Prediction Project
• xdatbus — A Python package enhancing VASP AIMD simulation
• xgdl — Explainability Library with Geometric Deep Learning for Scientific Tasks
• xymol — eXplain Your MOLecule (XYMOL): A Python package to understand and explain atom/bond contributions of small molecules in machine learning models.
• yEscher — Run gene knockouts and analyize S. Cerevisae, built on top of yeastGEM