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ORNL/Analysis-of-Large-Scale-Molecular-Datasets-with-Python

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10 stars·8 forks·Python·9 views

Analysis Of Large Scale Molecular Datasets With Python

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Features

  • Datasets and Databases - Workflow for generating and analyzing large-scale molecular datasets.

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Frequently asked questions

What does ornl/analysis-of-large-scale-molecular-datasets-with-python do?

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What are the main features of ornl/analysis-of-large-scale-molecular-datasets-with-python?

The main features of ornl/analysis-of-large-scale-molecular-datasets-with-python are: Datasets and Databases.

What are some open-source alternatives to ornl/analysis-of-large-scale-molecular-datasets-with-python?

Open-source alternatives to ornl/analysis-of-large-scale-molecular-datasets-with-python include: deepmodeling/ais-square. divelab/airs — [license-image]:https://img.shields.io/badge/license-GPL3.0-green.svg [license-url]:https://github.com/divelab/AIRS/blo… facebookresearch/fairchem — ocp is the Open Catalyst Project's library of state-of-the-art machine learning algorithms for catalysis. jla-gardner/load-atoms — load-atoms is a Python package for Loading Open Access Datasets for Atomistic Materials Science (LOAD-AtoMS). See the… materials-consortia/optimade — The OPTIMADE Specification. airi-institute/nabladft — nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset.