papers-for-molecular-design-using-DL
Molecular Design Database
An open-source resource gathering papers and information on using Generative AI and Deep Learning for molecular design and material design
List of Molecular and Material design using Generative AI and Deep Learning
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last commit: almost 2 years agoLinked from 1 awesome list
deep-generative-modelsdiffusiondrug-designenergy-based-modelgangenerative-aignnslstmmaterial-designmolecular-designprompt-learningreinforcement-learningrnnscore-based-generative-modelstransformervae
steven2358/awesome-generative-aiRelated projects:
| Repository | Description | Stars |
|---|---|---|
 mariewelt/openchem | A deep learning toolkit for computational chemistry and drug design research | 684 |
 choderalab/perses | An open-source software project exploring chemical space through advanced simulation methods and ensemble techniques. | 183 |
 baseflow/materialdesignhelpers | Provides pre-defined colors and dimensions for Material Design and Android Design guidelines | 13 |
 astrazeneca/chemicalx | A deep learning library for predicting the effects of combining two drugs | 719 |
 lukasturcani/stk | A Python library for designing and manipulating molecules, including automatic design and creation of databases. | 252 |
 shaharharel/cdn_molecule | Automates molecule design and drug discovery using machine learning models | 13 |
 materialsintelligence/mat2vec | Unsupervised word embeddings capture latent knowledge from materials science literature | 624 |
 zjulearning/graph_level_drug_discovery | A Python project that uses machine learning to improve the representation of molecules in drug discovery | 60 |
 atomistic-machine-learning/dtnn | An open-source Python framework for developing machine learning models to predict quantum-mechanical observables of molecular systems. | 78 |
 molecularai/aizynthfinder | A tool for retrosynthetic planning of chemical reactions | 603 |
 drorlab/atom3d | Enables machine learning on three-dimensional molecular structure by providing tools and datasets for working with 3D molecular data | 303 |
 aspuru-guzik-group/selfies | A Python library that provides a robust representation of semantically constrained graphs, specifically for molecules in chemistry. | 696 |
 joeddav/devol | An evolutionary algorithm for designing neural networks in Keras | 951 |
| atomistic-machine-learning/schnetpack | A toolbox for training and applying deep neural networks to predict atomistic properties of molecules and materials | 795 |
 jaechanglim/gnn_dti | This project implements a deep learning approach to predicting docking affinities for molecules with proteins | 66 |