Computational Biology Datasets Suitable For Machine Learning
This is a curated list of computational biology datasets that have been pre-processed for machine learning. This list is a work in progress, please submit a pull request for any dataset you would like to advertise!
Genotyping
| Name | Description | Comments |
|---|---|---|
| The Cancer Genome Atlas | Variety of Cancer Data | most cancer types have 100-1000 samples |
| NIH GDC | Cancer, many types of genomic data | |
| UK Biobank | ||
| European Genome-Phenome Archive | ||
| METABRIC | The genomic profiles (somatic mutations [targeted sequencing], copy number alterations, and gene expression) of 2509 breast cancers. | |
| HapMap | ||
| 23andMe | 2280 Public Domain Curated Genotypes | |
| Mice | SNPs, 2000+ samples | 4 generations. It might be possible to learn a family structure out of the data. |
| Arabidopsis | SNPs, 100+ phenotypes |
Promoter-Enhancer Pairs
| Name | Description | Comments |
|---|---|---|
| TargetFinder | ~100,000 DNA-DNA interaction pairs |
Gene/Protein Expression
| Name | Description | Comments |
|---|---|---|
| GEO | Main place for NCBI data | |
| ENCODE | Variety of assays to identify functional elements | |
| ArrayExpress | DNA sequencing, gene/protein expression, epigenetics | |
| Cytometry Continuous | flow cytometry data of 11 proteins+phospholipids, Discretized and cleaned data available offline | Classical benchmark dataset for learning graphical models; contains known errors |
| Transcription factor binding | ChIP-Seq data on 12 TFs | |
| GTEx | Landmark study for EQTL analysis | |
| PharmacoGenomics DB | ||
| ProteomeXChange | ||
| BeatAML | whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity | 672 tumour specimens collected from 562 patients |
Single-cell Data
| Name | Description | Comments |
|---|---|---|
| Single-cell expression atlas |
Regulatory Networks
| Name | Description | Comments |
|---|---|---|
| TRRUST | manually curated database of human transcriptional regulatory network | |
| Yeast Network | 23-million yeast 2-hybrid experiments to investigate genetic interactions | |
| Perturb-Seq | Integrated model of perturbations, single cell phenotypes, and epistatic interactions | |
| KEGG Metabolic Regulatory Network (Undirected) | 65554 instances, 29 attributes each | |
| KEGG Metabolic Regulatory Network (Directed) | 53414 instance, 24 attributes each |
Images
| Name | Description | Comments |
|---|---|---|
| The Cancer Imaging Archive | Extracts the images from the TCGA data | |
| Multiple Myeloma DREAM Challenge | Challenge to identify Multiple Myeloma Patients | |
| Breast Cancer Wisconsin (Diagnostic) Data Set | Predict whether the cancer is benign or malignant | |
| DDSM | Mammogram Database | |
| Kaggle Soft Tissue Sarcomas | Preprocessed subset of the TCIA study "Soft Tissue Sarcoma" | segmentation task |
| Kaggle Cervical Cancer Screening | Classify cervix type from images | |
| CMELYON17 | Pathology challenge - automated detection and classification of breast cancer metastases in whole-slide images of histological lymph node sections | |
| Grand Challenges | Datasets from biomedical image analysis competitions | |
| Breast Cancer MRI Dataset | Demographic, clinical, pathology, treatment, outcomes, and genomic data + MRI images |
fMRI
| Name | Description | Comments |
|---|---|---|
| ENGIMA Cerebellum | Goal: Examine the relationships between regional atrophy and motor and cognitive dysfunction | |
| Seizure Prediction | Goal: Classify EEG time series into pre-seizure vs. interictal (i.e., not preceding a seizure). |
Electronic Medical Records
| Name | Description | Comments |
|---|---|---|
| MIMIC | 59,000 EHRs | |
| UCI Diabetes | 130 US hospital data for 1999-2008 | |
| i2b2 | Clinical notes only, designed for NLP tasks | |
| PhysioNet | ||
| Metadata Acquired from Clinical Case Reports (MACCRs) | 3,100 curated clinical case reports spanning 15 disease groups and more than 750 reports of rare diseases | |
| eICU | 200k EHRs | |
| All of Us | >250k EHRs, some genomic data |
Radiographs
| Name | Description | Comments |
|---|---|---|
| CheXPert | 200k chest radiographs | Competition and leaderboard associated |
| MIMIC-CXR | ~400k chest x-rays, 14 labels | Data on PhysioNet |
| PadChest | 160k chest x-rays, 174 different findings |
Protein-Protein Interactions
| Name | Description | Comments |
|---|---|---|
| HINT (High-quality INTeractomes) | curated compilation of high-quality protein-protein interactions from 8 interactome resources |
Longitudinal Studies
| Name | Description | Comments |
|---|---|---|
| National Population Health Survey | Longitudinal Survey that collects health information via surveys every two years. |
Protein Structure
| Name | Description | Comments |
|---|---|---|
| ProteinNet | Standardized dataset for learning protein structure. Includes sequences, structures, alignments, PSSMs, and standardized train/test/valid splits. |
Natural Language Data
| Name | Description | Comments |
|---|---|---|
| BioASQ | Abstracts of medical articles (from PubMed); ontologies of medical concepts. | Tasks: MLC, QA. |
| Cases | Articles from medical case studies. | |
| UPMC Pathology | UPMC Pathology case studies. |
Therapeutics
| Name | Description | Comments |
|---|---|---|
| Therapeutic Data Commons | Many preprocessed datasets for therapeutic discovery, including target discovery, activity modeling, efficacy and safety, and manufacturing. | Available as Python modules. |