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Title: GitHub - AdaptInfer/CompBioDatasetsForMachineLearning: A Curated List of Computational Biology Datasets Suitable for Machine Learning

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X Title: GitHub - AdaptInfer/CompBioDatasetsForMachineLearning: A Curated List of Computational Biology Datasets Suitable for Machine Learning

Description: A Curated List of Computational Biology Datasets Suitable for Machine Learning - AdaptInfer/CompBioDatasetsForMachineLearning

Open Graph Description: A Curated List of Computational Biology Datasets Suitable for Machine Learning - AdaptInfer/CompBioDatasetsForMachineLearning

X Description: A Curated List of Computational Biology Datasets Suitable for Machine Learning - AdaptInfer/CompBioDatasetsForMachineLearning

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https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#computational-biology-datasets-suitable-for-machine-learning
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#genotyping
The Cancer Genome Atlashttps://cancergenome.nih.gov/
NIH GDChttps://gdc-portal.nci.nih.gov/
UK Biobankhttp://www.ukbiobank.ac.uk/about-biobank-uk/
European Genome-Phenome Archivehttps://www.ebi.ac.uk/ega/datasets
METABRIChttp://www.cbioportal.org/study?id=brca_metabric#summary
HapMaphttps://www.genome.gov/hapmap/
23andMehttp://www.biorxiv.org/content/early/2017/04/19/127241
Micehttp://wp.cs.ucl.ac.uk/outbredmice/heterogeneous-stock-mice/
Arabidopsishttps://www.arabidopsis.org/download/
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#promoter-enhancer-pairs
TargetFinderhttps://github.com/shwhalen/targetfinder
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#geneprotein-expression
GEOhttp://www.ncbi.nlm.nih.gov/geo/
ENCODEhttp://www.encodeproject.org/
ArrayExpresshttp://www.ebi.ac.uk/arrayexpress/
Cytometry Continuoushttp://science.sciencemag.org/content/308/5721/523
Transcription factor bindinghttp://www.pnas.org/content/106/51/21521.abstract?tab=ds
GTExhttp://www.gtexportal.org/home/
PharmacoGenomics DBhttps://www.pharmgkb.org/
ProteomeXChangehttp://www.proteomexchange.org/
BeatAMLhttps://www.nature.com/articles/s41586-018-0623-z
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#single-cell-data
Single-cell expression atlashttps://www.ebi.ac.uk/gxa/sc/
scPerturbhttps://www.nature.com/articles/s41592-023-02144-y
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#regulatory-networks
TRRUSThttp://www.grnpedia.org/trrust/
Yeast Networkhttp://science.sciencemag.org/content/353/6306/aaf1420/tab-pdf
Perturb-Seqhttp://www.sciencedirect.com/science/article/pii/S0092867416316105
KEGG Metabolic Regulatory Network (Undirected)https://archive.ics.uci.edu/ml/datasets/KEGG+Metabolic+Reaction+Network+%28Undirected%29
KEGG Metabolic Regulatory Network (Directed)https://archive.ics.uci.edu/ml/datasets/KEGG+Metabolic+Relation+Network+%28Directed%29
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#images
The Cancer Imaging Archivehttp://www.cancerimagingarchive.net/
Multiple Myeloma DREAM Challengehttps://www.synapse.org/#!Synapse:syn6187098/wiki/401884
Breast Cancer Wisconsin (Diagnostic) Data Sethttps://www.kaggle.com/uciml/breast-cancer-wisconsin-data
DDSMhttp://marathon.csee.usf.edu/Mammography/Database.html
Kaggle Soft Tissue Sarcomashttps://www.kaggle.com/4quant/soft-tissue-sarcoma
Kaggle Cervical Cancer Screeninghttps://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening
CMELYON17https://camelyon17.grand-challenge.org/
Grand Challengeshttps://grand-challenge.org/all_challenges/
Breast Cancer MRI Datasethttps://sites.duke.edu/mazurowski/resources/breast-cancer-mri-dataset/
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#fmri
ENGIMA Cerebellumhttps://my.vanderbilt.edu/enigmacerebellum/
Seizure Predictionhttps://www.kaggle.com/c/melbourne-university-seizure-prediction/data
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#electronic-medical-records
MIMIChttps://mimic.physionet.org/
UCI Diabeteshttps://archive.ics.uci.edu/ml/datasets/Diabetes+130-US+hospitals+for+years+1999-2008
i2b2https://www.i2b2.org/NLP/DataSets/Main.php
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Metadata Acquired from Clinical Case Reports (MACCRs)https://www.nature.com/articles/sdata2018258
eICUhttps://www.nature.com/articles/sdata2018178
All of Ushttps://databrowser.researchallofus.org/
PMC-Patientshttps://www.nature.com/articles/s41597-023-02814-8
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#radiographs
CheXPerthttps://stanfordmlgroup.github.io/competitions/chexpert/
MIMIC-CXRhttps://arxiv.org/abs/1901.07042
PadChesthttp://bimcv.cipf.es/bimcv-projects/padchest/
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#protein-protein-interactions
HINT (High-quality INTeractomes)http://hint.yulab.org/
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#longitudinal-studies
National Population Health Surveyhttp://www.statcan.gc.ca/eng/survey/household/3225
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#protein-structure
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https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#natural-language-data
BioASQhttp://www.bioasq.org/
Caseshttp://www.casesdatabase.com/
UPMC Pathologyhttp://path.upmc.edu/cases.html
https://github.com/AdaptInfer/CompBioDatasetsForMachineLearning#therapeutics
Therapeutic Data Commonshttps://tdcommons.ai/
Cancer Omics Drug Experiment Response Datasethttps://github.com/PNNL-CompBio/coderdata
standard schemahttps://github.com/PNNL-CompBio/coderdata/blob/main/schema/README.md
machine-learning https://github.com/topics/machine-learning
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