Foldingathome COVID-19 Datasets

Tutorials

• Folding@home COVID-19 efforts by Folding@home Consortium
  

Tools & Applications

• SARS-CoV-2 spike RBD with N501Y mutation bound to human ACE2 (953.7 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 COVID Moonshot absolute free energy calculations by The Voelz lab at Temple University
  
• SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) dimer simulations: A 2.9 ms dataset of the SARS-CoV-2 main viral protease (apo, dimer) in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) monomer simulations: A 2.6 ms equilibrium dataset of the SARS-CoV-2 main viral protease (apo, monomer) by The Chodera lab at MSKCC
  
• SARS-CoV-2 main viral protease (Mpro, 3CLPro, nsp5) monomer simulations: A 6.4 ms dataset of the SARS-CoV-2 main viral protease (apo, monomer) in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp10 dataset: A 6.1 ms dataset of the SARS-CoV-2 nsp10 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp3 macrodomain dataset: An 11 ms dataset of the SARS-CoV-2 nsp3 macrodomain in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp3 pl2pro domain dataset: An 731 µs dataset of the SARS-CoV-2 nsp3 pl2pro domain in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp7 simulations: A 3.7 ms dataset of the SARS-CoV-2 nsp7 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp8 simulations: A 1.8 ms dataset of the SARS-CoV-2 nsp8 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 nsp9 simulations: A 9 ms dataset of the SARS-CoV-2 nsp9 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 RNA polymerase (nsp12, RdRP) dataset: A 3.4 ms dataset of the SARS-CoV-2 nsp12 protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 spike protein dataset: A 1.2 ms dataset of the SARS-CoV-2 spike protein in search of cryptic pockets by The Bowman lab at Washington University in St. Louis
  
• SARS-CoV-2 spike RBD (with glycosylation) (1.8 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD (without glycosylation) (1.9 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD bound to human ACE2 receptor (173.8 us): Wild-type and mutant simulations by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD bound to monoclonal antibody S2H97 (623.7 us) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD bound to monoclonal antibody S309 (1.1 ms) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD with P337A mutation bound to monoclonal antibody S309 (907.0 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  
• SARS-CoV-2 spike RBD with P337L mutation bound to monoclonal antibody S309 (923.2 µs) by The Chodera lab at the Memorial Sloan Kettering Cancer Center
  

Publications

• Circulating SARS-CoV-2 spike N439K variants maintain fitness while evading antibody-mediated immunity by Emma C. Thomson, Laura E, Rosen, James G. Shepherd, et al.
  
• SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape by Tyler N. Starr, Nadine Czudnochowski, Zhuoming Liu, et al.
  
• SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome by Maxwell I. Zimmerman, Justin R. Porter, Michael D. Ward, Sukrit Singh, Neha Vithani, Artur Meller, Upasana L. Mallimadugula, Catherine E. Kuhn, Jonathan H. Borowsky, View ORCID ProfileRafal P. Wiewiora, Matthew F. D. Hurley, Aoife M Harbison, Carl A Fogarty, Joseph E. Coffland, Elisa Fadda, Vincent A. Voelz, John D. Chodera, Gregory R. Bowman
  

PubSeq - Public Sequence Resource

Tutorials

• PubSeq Documentation by PubSeq development team
  
• PubSeq FAQ by PubSeq development team
  
• Query metadata by PubSeq development team
  
• REST API by PubSeq development team
  
• Submitting a sequence by PubSeq development team
  

Tools & Applications

• Source code for (meta)data uploader by PubSeq development team
  
• Source code for CWL workflows by PubSeq development team
  
• Source code for website by PubSeq development team
  

Publications

• Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 during Border Quarantine and Air Travel, New Zealand (Aotearoa) by Eichler, N. et al.
  

NYU Langone & FAIR FastMRI Dataset

Tutorials

• FastMRI Tutorial (Jupyter Notebook) by Tullie Murrell
  
• How to Get Started Working with the FastMRI Dataset (and why you should!) by Kevin Hodges
  

Publications

• Advancing machine learning for MR image reconstruction with an open competition:Overview of the 2019 fastMRI challenge by Knoll et al (2020)
  
• Assessment of the generalization of learned image reconstruction and the potential for transfer learning. by Knoll et al (2019)
  
• Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction by Knoll et al (2019)
  
• fastMRI:An Open Dataset and Benchmarks for Accelerated MRI by Zbontar et al (2019)
  

Basic Local Alignment Sequences Tool (BLAST) Databases

Tools & Applications

• BLAST on the Cloud with NCBI’s ElasticBLAST by Sixing Huang
  
• BLAST+ Docker by NCBI BLAST
  

Publications

• BLAST+: Architecture and Applications by Christiam Camacho 1 , George Coulouris, Vahram Avagyan, Ning Ma, Jason Papadopoulos, Kevin Bealer, Thomas L Madden
  
• Gapped BLAST and PSI-BLAST: A New Generation of Protein Database Search Programs by S F Altschul, T L Madden, A A Schäffer, J Zhang, Z Zhang, W Miller, D J Lipman
  

Synthea synthetic patient generator data in OMOP Common Data Model

Tutorials

• Create data science environments on AWS for health analysis using OHDSI by James Wiggins
  AWS CloudFormationAmazon EC2Amazon RDS
• Map clinical notes to the OMOP Common Data Model and healthcare ontologies using Amazon Comprehend Medical by James Wiggins
  Amazon ComprehendAWS CloudFormationAmazon EC2Amazon RDS
• Predict patient health outcomes using OHDSI and machine learning on AWS by James Wiggins
  AWS CloudFormationAmazon EC2Amazon RDS

Tools & Applications

• OHDSIonAWS by James Wiggins
  

MIMIC-III (‘Medical Information Mart for Intensive Care’)

Tutorials

• Building predictive disease models using Amazon SageMaker with Amazon HealthLake normalized data by Ujjwal Ratan, Nihir Chadderwala, and Parminder Bhatia
  AWS GlueAWS HealthLakeAmazon SageMaker
• Perform biomedical informatics without a database using MIMIC-III data and Amazon Athena by James Wiggins, Alistair Johnson
  Amazon AthenaAWS Glue

Tools & Applications

• MIMIC-code GitHub repository by Alistair Johnson
  

Medical Segmentation Decathlon

Tutorials

• Pytorch-Integrated MSD Data Loader by MONAI Development Team
  

Tools & Applications

• MONAI: Getting Started by MONAI Development Team
  

Publications

• A large annotated medical image dataset for the development and evaluation of segmentation algorithms by Simpson A. L., Antonelli M., Bakas S., Bilello M., Farahana K., van Ginneken B., et al
  

QIIME 2 Tutorial Data

Tutorials

• Developing with QIIME 2 by Caporaso and Bolyen
  
• QIIME 2 User Documentation (currently being replaced by *Using QIIME 2*) by The QIIME 2 Development Team
  
• Using QIIME 2 by Caporaso Lab
  

COVID-19 Data Lake

Tutorials

• A public data lake for analysis of COVID-19 data by AWS Data Lake Team
  AWS GlueAmazon AthenaAmazon ComprehendAmazon KendraAmazon QuickSight
• Exploring the public AWS COVID-19 data lake by AWS Data Lake Team
  Amazon AthenaAWS GlueAmazon SageMaker
• How to use SQL to query data in S3 Bucket with Amazon Athena and AWS SDK for .NET by AWS ProServe US West Applications Team
  Amazon AthenaAWS GlueAmazon S3AWS CloudFormation

Tools & Applications

• CloudFormation template for Glue Catalog table definitions by AWS Data Lake Team
  
• Explore the COVID-19 data lake public S3 bucket by AWS Data Lake Team
  

DNAStack COVID19 SRA Data

Tutorials

• Viral lineage assignment by Heather Ward
  AWS BatchAmazon EC2Amazon S3

Tools & Applications

• Viral AI by DNAstack
  

EMory BrEast Imaging Dataset (EMBED)

Tutorials

• Sample Notebook by Emory-HITI
  

Publications

• The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.4M Screening and Diagnostic Mammograms by Jiwoong J. Jeong, Brianna L. Vey, Ananth Reddy, Thomas Kim, Thiago Santos, Ramon Correa, Raman Dutt, Marina Mosunjac, Gabriela Oprea-Ilies, Geoffrey Smith, Minjae Woo, Christopher R. McAdams, Mary S. Newell, Imon Banerjee, Judy Gichoya, Hari Trivedi
  

Emory Knee Radiograph (MRKR) dataset

Tutorials

• Example Notebook by Emory-HITI
  

Publications

• Emory Knee Radiograph Dataset by Brandon Price, Jason Adleberg, Kaesha Thomas, Zach Zaiman, Aawez Mansuri, Beatrice Brown-Mulry, Chima Okecheukwu, Judy Gichoya, Hari Trivedi.
  

Reference data for HiFi human WGS

Tutorials

• PacBio WGS Variant Pipeline README by Pacific Biosciences of California, Inc
  

Tools & Applications

• Consolidated analysis with the PacBio WGS Variant Pipeline by Pacific Biosciences of California, Inc
  

Tabula Sapiens

Publications

• Tabula Sapiens reveals transcription factor expression, senescence effects, and sex-specific features in cell types from 28 human organs and tissues by The Tabula Sapiens Consortium, Stephen R Quake
  
• The Tabula Sapiens: a multiple organ single cell transcriptomic atlas of humans by The Tabula Sapiens Consortium
  

CMS 2008-2010 Data Entrepreneurs’ Synthetic Public Use File (DE-SynPUF) in OMOP Common Data Model

Tutorials

• Create data science environments on AWS for health analysis using OHDSI by James Wiggins
  AWS CloudFormationAmazon EC2Amazon RDS
• Map clinical notes to the OMOP Common Data Model and healthcare ontologies using Amazon Comprehend Medical by James Wiggins
  Amazon ComprehendAWS CloudFormationAmazon EC2Amazon RDS
• Predict patient health outcomes using OHDSI and machine learning on AWS by James Wiggins
  AWS CloudFormationAmazon EC2Amazon RDS

Tools & Applications

• OHDSIonAWS by James Wiggins
  

COVID-19 Genome Sequence Dataset

Tools & Applications

• Download SRA sequence data using Amazon Web Services (AWS) by NCBI SRA
  

NYUMets Brain Dataset

Publications

• Longitudinal deep neural networks for assessing metastatic brain cancer on a massive open benchmark. by Link et al (2023)
  

Synthea Coherent Data Set

Publications

• The “Coherent Data Set”: Combining Patient Data and Imaging in a Comprehensive Synthetic Health Record. by Walonoski J, Hall D, Bates KM, Farris MH, Dagher J, Downs ME, Sivek RT, Wellner B, Gregorowicz A, Hadley M, Campion FX, Levine L, Wacome K, Emmer G, Kemmer A, Malik M, Hughes J, Granger E, Russell S.
  

Tabula Muris

Publications

• Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. by Tabula Muris Consortium (2019)
  

Tabula Muris Senis

Tutorials

• Fast queries of scRNAseq datasets with Amazon Athena by Andrew Ang, James Golden, Lisa McFerrin, and Lee Pang
  Amazon AthenaAWS Glue

VitalDB

Publications

• VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients by Hyung-Chul Lee, Yoonsang Park, Soo Bin Yoon, Seong Mi Yang, Dongnyeok Park, and Chul-Woo Jung
  

SatPM2.5

Tutorials

• Importing and Plotting the V6.GL.02.03 dataset into Matlab by Aaron van Donkelaar
  

Publications

• Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning by Siyuan Shen, Chi Li, Aaron van Donkelaar, Nathan Jacobs, Chenguang Wang, and Randall V. Martin