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Reload to refresh your session. {{ message }} Mariewelt / OpenChem Public * Notifications * Fork 104 * Star 571 OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research mariewelt.github.io/openchem/ License MIT license 571 stars 104 forks Activity Star Notifications * Code * Issues 15 * Pull requests 1 * Actions * Projects 0 * Wiki * Security * Insights More * Code * Issues * Pull requests * Actions * Projects * Wiki * Security * Insights Mariewelt/OpenChem This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. master Switch branches/tags [ ] Branches Tags Could not load branches Nothing to show {{ refName }} default View all branches Could not load tags Nothing to show {{ refName }} default View all tags Name already in use A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. 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Type Name Latest commit message Commit time benchmark_datasets small version of chembl dataset March 11, 2021 02:27 devtools Added devtools February 19, 2019 16:17 docs Add files via upload March 11, 2021 08:01 example_configs pretrained parameters for molecular rnn March 10, 2021 22:56 logs pretrained parameters for molecular rnn March 10, 2021 22:56 openchem pretrained parameters for molecular rnn March 10, 2021 22:56 .gitignore updated .gitignore file November 3, 2020 15:00 .travis.yml Fixed path to the folder with unit tests February 19, 2019 16:41 Dockerfile Dockerfile November 3, 2020 15:00 LICENSE Update LICENSE April 27, 2022 15:27 README.md Update README.md March 11, 2021 08:14 launch.py fixed issue with hanging processes after KeyboardInterrupt November 3, 2020 14:17 requirements.txt Merge branch 'develop' into tmp February 24, 2019 10:57 run.py added 'predict' run mode, updated data layers and models accrodingly November 3, 2020 13:45 setup.py fixed tensorboard dependency November 6, 2020 08:33 View code [ ] OpenChem Main features Documentation Supported functionality Tasks: Data types Modules: Installation Requirements General installation Installation with Docker Publications Acknowledgements README.md OpenChem OpenChem OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend. The goal of OpenChem is to make Deep Learning models an easy-to-use tool for Computational Chemistry and Drug Design Researchers. Main features * Modular design with unified API, modules can be easily combined with each other. * OpenChem is easy-to-use: new models are built with only configuration file. * Fast training with multi-gpu support. * Utilities for data preprocessing. * Tensorboard support. Documentation Check out OpenChem documentation here. Supported functionality Tasks: * Classification (binary or multi-class) * Regression * Multi-task (such as N binary classification tasks) * Generative models Data types * Sequences of characters such as SMILES strings or amino-acid sequences * Molecular graphs. OpenChem takes care of converting SMILES strings into molecular graphs Modules: * Token embeddings * Recurrent neural network encoders * Graph convolution neural network encoders * Multi-layer perceptrons We are working on populating OpenChem with more models and other building blocks. Installation Requirements In order to get started you need: * Modern NVIDIA GPU, compute capability 3.5 or newer. * Python 3.5 or newer (we recommend Anaconda distribution) * CUDA 9.0 or newer General installation If you installed your Python with Anaconda you can run the following commands to get started: git clone https://github.com/Mariewelt/OpenChem.git cd OpenChem conda create --name OpenChem python=3.7 conda activate OpenChem conda install --yes --file requirements.txt conda install -c rdkit rdkit nox cairo conda install pytorch torchvision -c pytorch pip install -e . If your CUDA version is older than 9.0, check Pytorch website for different installation instructions. Installation with Docker Alternative way of installation is with Docker. We provide a Dockerfile, so you can run your models in a container that already has all the necessary packages installed. You will also need nvidia-docker in order to run models on GPU. Publications If you use OpenChem in your projects, please cite: Korshunova, Maria, et al. "OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design." Journal of Chemical Information and Modeling 61.1 (2021): 7-13. MolecularRNN model paper: Popova, Mariya, et al. "MolecularRNN: Generating realistic molecular graphs with optimized properties." arXiv preprint arXiv:1905.13372 (2019). Acknowledgements OpenChem was supported by Carnegie Mellon University, the University of North Carolina at Chapel Hill and NVIDIA Corp. CMU UNC NVIDIA About OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research mariewelt.github.io/OpenChem/ Topics machine-learning deep-neural-networks deep-learning computational-biology pytorch computational-chemistry drug-discovery drug-design predictive-modeling graph-convolutional-networks qsar Resources Readme License MIT license Activity Stars 571 stars Watchers 35 watching Forks 104 forks Report repository Releases No releases published Packages 0 No packages published Contributors 2 * @Mariewelt Mariewelt Maria Korshunova * @itisAliRH itisAliRH Alireza Heidari Languages * Python 98.9% * Other 1.1% Footer (c) 2023 GitHub, Inc. Footer navigation * Terms * Privacy * Security * Status * Docs * Contact GitHub * Pricing * API * Training * Blog * About You can't perform that action at this time.