SARS-CoV2 Docking Dataset for MLMol Language Model (50M)

Tsaris, Aristeidis; Gounley, John; Blanchard, Andrew

doi:10.13139/ORNLNCCS/1868526

Title: SARS-CoV2 Docking Dataset for MLMol Language Model (50M)

Dataset
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Abstract

This is a processed molecular dataset from this https://doi.ccs.ornl.gov/ui/doi/348 adding up to 50M molecules for the training and 486K molecules for the validation. Instructions on how to use/run/train this dataset can be found here: https://code.ornl.gov/candle/mlmol

Authors:

Tsaris, Aristeidis; Gounley, John; Blanchard, Andrew

ORNL-OLCF

Publication Date:: Fri May 20 04:00:00 UTC 2022

DOE Contract Number:: AC05-00OR22725

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: Office of Science (SC)

OSTI Identifier:: 1868526

DOI:: https://doi.org/10.13139/ORNLNCCS/1868526

Citation Formats


                    Tsaris, Aristeidis, Gounley, John, and Blanchard, Andrew. SARS-CoV2 Docking Dataset for MLMol Language Model (50M).  United States: N. p., 2022. 
        Web.  doi:10.13139/ORNLNCCS/1868526.

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                    Tsaris, Aristeidis, Gounley, John, & Blanchard, Andrew. SARS-CoV2 Docking Dataset for MLMol Language Model (50M).  United States.  doi:https://doi.org/10.13139/ORNLNCCS/1868526

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                    Tsaris, Aristeidis, Gounley, John, and Blanchard, Andrew. 2022.  
"SARS-CoV2 Docking Dataset for MLMol Language Model (50M)".  United States.  doi:https://doi.org/10.13139/ORNLNCCS/1868526.  https://www.osti.gov/servlets/purl/1868526. Pub date:Fri May 20 04:00:00 UTC 2022

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@article{osti_1868526,

  title        = {SARS-CoV2 Docking Dataset for MLMol Language Model (50M)},

  author       = {Tsaris, Aristeidis and Gounley, John and Blanchard, Andrew},

  abstractNote = {This is a processed molecular dataset from this https://doi.ccs.ornl.gov/ui/doi/348 adding up to 50M molecules for the training and 486K molecules for the validation. Instructions on how to use/run/train this dataset can be found here: https://code.ornl.gov/candle/mlmol},

  doi          = {10.13139/ORNLNCCS/1868526},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri May 20 04:00:00 UTC 2022},

  month        = {Fri May 20 04:00:00 UTC 2022}

}

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DOI: https://doi.org/10.13139/ORNLNCCS/1868526

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