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---
title: "Resources"
task: ""
lineage_type: import
upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/data/resources.json
upstream_sha: 7a064bf0
imported_at: 2026-08-08
prompt_class: catalogue
upstream_changes: accepted
author: upstream
validated: false
---
[
{
"id": "chembl_web_services",
"name": "ChEMBL Web Services",
"type": "api",
"url": "https://www.ebi.ac.uk/chembl/ws",
"description": "REST API for bioactive molecules, targets, and bioassays.",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"chemical-structure"
],
"organism": [],
"api": true,
"entities": [
"molecule",
"protein"
],
"documentation": "https://www.ebi.ac.uk/chembl/api/data/docs",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.ebi.ac.uk/chembl/api/data/docs"
]
},
{
"id": "clinicaltrials_gov_api",
"name": "ClinicalTrials.gov API",
"type": "api",
"url": "https://clinicaltrials.gov/api/gui",
"description": "API for querying clinical trial metadata and results.",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"clinical"
],
"organism": [],
"api": true,
"entities": [
"disease",
"drug"
],
"documentation": "https://clinicaltrials.gov/data-api/api",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://clinicaltrials.gov/data-api/api"
]
},
{
"id": "ensembl_rest_api",
"name": "Ensembl REST API",
"type": "api",
"url": "https://rest.ensembl.org/",
"description": "API for genomic annotations, variants, genes, and comparative genomics.",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"genomics"
],
"organism": [],
"api": true,
"entities": [
"gene",
"genome",
"transcript",
"variant"
],
"documentation": "https://rest.ensembl.org/",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://rest.ensembl.org/"
]
},
{
"id": "kegg_rest_api",
"name": "KEGG REST API",
"type": "api",
"url": "https://www.kegg.jp/kegg/rest/keggapi.html",
"description": "API for accessing KEGG pathways, compounds, genes, and reactions.",
"tags": [
"api"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": true,
"entities": [
"compound",
"gene",
"pathway"
],
"documentation": "https://www.kegg.jp/kegg/rest/keggapi.html",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.kegg.jp/kegg/rest/keggapi.html"
]
},
{
"id": "ncbi_e_utilities",
"name": "NCBI E-utilities",
"type": "api",
"url": "https://www.ncbi.nlm.nih.gov/books/NBK25501/",
"description": "Unified APIs for accessing NCBI databases (Gene, GEO, SRA, PubChem, etc).",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"genomics",
"transcriptomics"
],
"organism": [],
"api": true,
"entities": [
"gene",
"genome",
"protein",
"transcript",
"variant"
],
"documentation": "https://www.ncbi.nlm.nih.gov/books/NBK25501/",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.ncbi.nlm.nih.gov/books/NBK25501/"
]
},
{
"id": "open_targets_platform_api",
"name": "Open Targets Platform API",
"type": "api",
"url": "https://platform.opentargets.org/api",
"description": "API for targetโ€“disease associations integrating genetics, genomics, and drug data.",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"genomics",
"knowledge-graph"
],
"organism": [],
"api": true,
"entities": [
"disease",
"drug",
"gene",
"variant"
],
"documentation": "https://platform.opentargets.org/api",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://platform.opentargets.org/api"
]
},
{
"id": "pubmed_e_utilities_esearch_efetch",
"name": "PubMed E-utilities (esearch/efetch)",
"type": "api",
"url": "https://www.nlm.nih.gov/dataguide/edirect/esearch.html",
"description": "APIs for searching and retrieving biomedical literature from PubMed.",
"tags": [
"api"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": true,
"documentation": "https://www.ncbi.nlm.nih.gov/books/NBK25501/",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.ncbi.nlm.nih.gov/books/NBK25501/"
]
},
{
"id": "uniprot_rest_api",
"name": "UniProt REST API",
"type": "api",
"url": "https://www.uniprot.org/help/api",
"description": "Programmatic access to protein sequence and functional annotation data.",
"tags": [
"api"
],
"tasks": [],
"modalities": [
"protein-sequence",
"proteomics"
],
"organism": [],
"api": true,
"entities": [
"protein"
],
"documentation": "https://www.uniprot.org/help/api",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.uniprot.org/help/api"
]
},
{
"id": "1000_genomes_project",
"name": "1000 Genomes Project",
"type": "benchmark",
"url": "https://www.internationalgenome.org/",
"description": "Reference panel of human genetic variation from 2,504 individuals across 26 populations.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "bace",
"name": "BACE",
"type": "benchmark",
"url": "https://www.kaggle.com/datasets/gokturkkoch/bace",
"description": "Binary classification and regression dataset for ฮฒ-secretase 1 (BACE-1) inhibitor binding affinity.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"classification",
"regression"
],
"modalities": [
"chemical-structure"
],
"organism": [],
"api": false,
"entities": [
"molecule",
"protein"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.kaggle.com/datasets/gokturkkoch/bace"
]
},
{
"id": "beat_aml",
"name": "BEAT AML",
"type": "benchmark",
"url": "https://biodev.github.io/BeatAML2/",
"description": "Functional ex vivo drug sensitivity measurements paired with genomics for acute myeloid leukemia.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"drug-response-prediction"
],
"modalities": [
"genomics"
],
"organism": [],
"api": false,
"entities": [
"cell",
"disease",
"drug",
"gene"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://biodev.github.io/BeatAML2/"
]
},
{
"id": "bento",
"name": "Bento",
"type": "benchmark",
"url": "https://github.com/LigandPro/Bento",
"description": "Protein-ligand docking benchmark covering rigid, flexible, de novo, blind, induced-fit, and covalent docking tasks.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "bindingdb_curated_sets",
"name": "BindingDB Curated Sets",
"type": "benchmark",
"url": "https://www.bindingdb.org/rwd/bind/chemsearch/marvin/SDFdownload.jsp?all_download=yes",
"description": "Curated binding affinity datasets for proteinโ€“ligand interaction benchmarking.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"drug-target-interaction"
],
"modalities": [
"chemical-structure"
],
"organism": [],
"api": false,
"entities": [
"molecule",
"protein"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.bindingdb.org/"
]
},
{
"id": "cancer_therapeutics_response_portal_ctrp",
"name": "Cancer Therapeutics Response Portal (CTRP)",
"type": "benchmark",
"url": "https://portals.broadinstitute.org/ctrp/",
"description": "Drug sensitivity profiles across ~900 cancer cell lines for >400 compounds.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"drug-response-prediction"
],
"modalities": [],
"organism": [],
"api": false,
"entities": [
"cell",
"drug"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://portals.broadinstitute.org/ctrp/"
]
},
{
"id": "clintox",
"name": "ClinTox",
"type": "benchmark",
"url": "https://tdcommons.ai/single_pred_tasks/tox/#clintox",
"description": "Clinical toxicity dataset contrasting FDA-approved drugs with those that failed clinical trials due to toxicity.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"classification"
],
"modalities": [
"clinical"
],
"organism": [],
"api": false,
"entities": [
"drug"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://tdcommons.ai/single_pred_tasks/tox/#clintox"
]
},
{
"id": "cptac_clinical_proteomic_tumor_analysis_consortium",
"name": "CPTAC (Clinical Proteomic Tumor Analysis Consortium)",
"type": "benchmark",
"url": "https://proteomics.cancer.gov/programs/cptac",
"description": "Multi-omic proteogenomic datasets for multiple cancer types linking proteomics with genomics.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "crossdocked2020",
"name": "CrossDocked2020",
"type": "benchmark",
"url": "https://arxiv.org/abs/2001.01037",
"description": "Large-scale dataset for structure-based virtual screening.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "dud_e_directory_of_useful_decoys_enhanced",
"name": "DUD-E (Directory of Useful Decoys, Enhanced)",
"type": "benchmark",
"url": "http://dude.docking.org/",
"description": "Structure-based virtual screening benchmark with active ligands and challenging decoy sets across diverse protein targets.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "flip_fitness_landscape_inference_for_proteins",
"name": "FLIP (Fitness Landscape Inference for Proteins)",
"type": "benchmark",
"url": "https://github.com/J-SNACKKB/FLIP",
"description": "Benchmark collection of protein fitness landscape datasets for evaluating protein ML models.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "guacamol",
"name": "GuacaMol",
"type": "benchmark",
"url": "https://github.com/BenevolentAI/guacamol",
"description": "Benchmark suite for generative molecular design models.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"molecular-generation"
],
"modalities": [
"chemical-structure"
],
"organism": [],
"api": false,
"entities": [
"molecule"
],
"github": "https://github.com/BenevolentAI/guacamol",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://github.com/BenevolentAI/guacamol"
]
},
{
"id": "hest_xenium_virtual_spatial_transcriptomics",
"name": "HEST Xenium virtual spatial transcriptomics",
"type": "benchmark",
"url": "https://huggingface.co/datasets/ratschlab/HEST_Xenium_virtual_spatial_transcriptomics",
"description": "DeepSpot-M predicted transcriptome-wide ST for 59 HEST-1k 10x Xenium samples (~13.3M cells) (gated). Paper: [DeepSpot-M](https://www.medrxiv.org/content/10.64898/2026.06.19.26356060v1).",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"regression"
],
"modalities": [
"histopathology",
"spatial-transcriptomics",
"transcriptomics"
],
"organism": [],
"api": false,
"entities": [
"cell",
"gene",
"tissue"
],
"documentation": "https://huggingface.co/datasets/ratschlab/HEST_Xenium_virtual_spatial_transcriptomics",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://huggingface.co/datasets/ratschlab/HEST_Xenium_virtual_spatial_transcriptomics"
]
},
{
"id": "jump_cell_painting_datasets",
"name": "JUMP Cell Painting Datasets",
"type": "benchmark",
"url": "https://github.com/jump-cellpainting/datasets",
"description": "Consortium-scale cell imaging perturbation datasets (chemical and genetic) for phenotypic profiling and drug discovery research.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "lincs_l1000",
"name": "LINCS L1000",
"type": "benchmark",
"url": "https://lincsproject.org/LINCS/tools/workflows/find-the-best-place-to-obtain-the-lincs-l1000-data",
"description": "Gene expression profiles (978 landmark genes) for >20,000 chemical and genetic perturbations across cell lines.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"perturbation-prediction"
],
"modalities": [
"transcriptomics"
],
"organism": [],
"api": false,
"entities": [
"cell",
"compound",
"gene"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://lincsproject.org/LINCS/tools/workflows/find-the-best-place-to-obtain-the-lincs-l1000-data"
]
},
{
"id": "moleculenet",
"name": "MoleculeNet",
"type": "benchmark",
"url": "http://moleculenet.ai/",
"description": "Benchmark datasets for molecular machine learning.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"classification",
"regression"
],
"modalities": [
"chemical-structure"
],
"organism": [],
"api": false,
"entities": [
"molecule"
],
"github": "https://github.com/deepchem/moleculenet",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://github.com/deepchem/moleculenet"
]
},
{
"id": "moses",
"name": "MOSES",
"type": "benchmark",
"url": "https://github.com/molecularsets/moses",
"description": "Benchmarking platform for molecular generation models.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "ogb_open_graph_benchmark",
"name": "OGB (Open Graph Benchmark)",
"type": "benchmark",
"url": "https://ogb.stanford.edu/",
"description": "Large-scale graph ML benchmark suite including biological datasets such as ogbl-ppa (protein-protein associations) and ogbg-molhiv.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "openbiolink",
"name": "OpenBioLink",
"type": "benchmark",
"url": "https://github.com/OpenBioLink/OpenBioLink",
"description": "Benchmark datasets for biological knowledge graph completion.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "pharmgkb",
"name": "PharmGKB",
"type": "benchmark",
"url": "https://www.pharmgkb.org/",
"description": "Curated pharmacogenomics dataset linking genetic variants to drug response phenotypes across thousands of drugs.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"drug-response-prediction"
],
"modalities": [
"clinical",
"genomics"
],
"organism": [],
"api": false,
"entities": [
"drug",
"gene",
"phenotype",
"variant"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://www.pharmgkb.org/"
]
},
{
"id": "pk_db",
"name": "PK-DB",
"type": "benchmark",
"url": "https://pk-db.com/",
"description": "Open database of experimental pharmacokinetics (PK) and ADME data from clinical and preclinical studies.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [
"clinical"
],
"organism": [],
"api": false,
"entities": [
"drug"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://pk-db.com/"
]
},
{
"id": "prism",
"name": "PRISM",
"type": "benchmark",
"url": "https://depmap.org/portal/prism/",
"description": "Cancer drug sensitivity profiling of >4,500 drugs across >900 cancer cell lines using pooled-cell-line barcoding.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"drug-response-prediction"
],
"modalities": [],
"organism": [],
"api": false,
"entities": [
"cell",
"drug"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"https://depmap.org/portal/prism/"
]
},
{
"id": "proteingym",
"name": "ProteinGym",
"type": "benchmark",
"url": "https://github.com/OATML-Markslab/ProteinGym",
"description": "Large-scale benchmark of deep mutational scanning assays for evaluating protein fitness landscape models.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"regression"
],
"modalities": [
"protein-sequence"
],
"organism": [],
"api": false,
"entities": [
"protein"
],
"github": "https://github.com/OATML-Markslab/ProteinGym",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://github.com/OATML-Markslab/ProteinGym"
]
},
{
"id": "qm9",
"name": "QM9",
"type": "benchmark",
"url": "https://figshare.com/collections/Quantum_chemistry_structures_and_properties_of_134_kilo_molecules/978904",
"description": "Quantum chemistry properties for 134K stable small organic molecules computed at DFT level.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "scib_single_cell_integration_benchmarks",
"name": "scIB (Single-cell Integration Benchmarks)",
"type": "benchmark",
"url": "https://github.com/theislab/scib",
"description": "Comprehensive benchmarking framework for single-cell data integration methods.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "scperturb",
"name": "scPerturb",
"type": "benchmark",
"url": "https://github.com/sanderlab/scPerturb",
"description": "Curated and continuously updated single-cell perturbation data resource spanning CRISPR and drug perturbation studies.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [
"perturbation-prediction"
],
"modalities": [
"single-cell-rna-seq"
],
"organism": [],
"api": false,
"entities": [
"cell",
"drug",
"gene"
],
"github": "https://github.com/sanderlab/scPerturb",
"last_checked": "2026-08-08",
"metadata_sources": [
"https://github.com/sanderlab/scPerturb"
]
},
{
"id": "sider_side_effect_resource",
"name": "SIDER (Side Effect Resource)",
"type": "benchmark",
"url": "http://sideeffects.embl.de/",
"description": "Database of 1,430 approved drugs with their recorded adverse drug reactions across 27 system-organ classes.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [
"clinical"
],
"organism": [],
"api": false,
"entities": [
"drug",
"phenotype"
],
"last_checked": "2026-08-08",
"metadata_sources": [
"http://sideeffects.embl.de/"
]
},
{
"id": "tabula_muris",
"name": "Tabula Muris",
"type": "benchmark",
"url": "https://tabula-muris.ds.czbiohub.org/",
"description": "Comprehensive single-cell atlas of 20 mouse organs and tissues, enabling cross-tissue and cross-species comparisons.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "tabula_sapiens",
"name": "Tabula Sapiens",
"type": "benchmark",
"url": "https://tabula-sapiens-portal.ds.czbiohub.org/",
"description": "Comprehensive human single-cell atlas of ~500K cells from 24 organs and tissues across multiple donors.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "tape_tasks_assessing_protein_embeddings",
"name": "TAPE (Tasks Assessing Protein Embeddings)",
"type": "benchmark",
"url": "https://github.com/songlab-cal/tape",
"description": "Benchmark suite of five biologically meaningful semi-supervised learning tasks for evaluating protein representations.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "tcga_virtual_spatial_transcriptomics_atlas",
"name": "TCGA virtual spatial transcriptomics atlas",
"type": "benchmark",
"url": "https://huggingface.co/datasets/ratschlab/TCGA_virtual_spatial_transcriptomics_atlas",
"description": "DeepSpot-M predicted transcriptome-wide ST for TCGA H&E (FF + FFPE; 28,664 slides / 32 cancer types; gated). Paper: [DeepSpot-M](https://www.medrxiv.org/content/10.64898/2026.06.19.26356060v1).",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "the_cancer_genome_atlas_tcga",
"name": "The Cancer Genome Atlas (TCGA)",
"type": "benchmark",
"url": "https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga",
"description": "Comprehensive multi-omics (genomics, transcriptomics, proteomics, methylation) dataset for 33 cancer types across ~11,000 patients.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "therapeutics_data_commons_tdc",
"name": "Therapeutics Data Commons (TDC)",
"type": "benchmark",
"url": "https://tdcommons.ai/",
"description": "Unified benchmark suite covering ADMET, drug-target interaction, drug response, and more.",
"tags": [
"benchmarks-and-datasets"
],
"tasks": [],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "tox21",
"name": "Tox21",
"type": "benchmark",
"url": "https://tripod.nih.gov/tox21/challenge/",
"description": "12,707 compounds tested in 12 nuclear receptor and stress-response pathway biochemical assays for toxicity prediction.",
"tags": [
"benchmarks-and-datasets"
],
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{
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{
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{
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"interaction"
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{
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{
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{
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],
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{
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],
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{
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{
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{
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"interaction"
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"gene"
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{
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],
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},
{
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],
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},
{
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],
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},
{
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],
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{
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],
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],
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{
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{
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],
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{
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"interaction"
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"Small Molecule"
],
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{
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],
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{
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],
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},
{
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],
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],
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{
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],
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],
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{
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],
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},
{
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],
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{
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"tags": [
"compound"
],
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"Small Molecule"
],
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},
{
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],
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"chemical-structure"
],
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"disease",
"drug",
"protein"
],
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]
},
{
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"compound"
],
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"Small Molecule"
],
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},
{
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"compound"
],
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"Small Molecule"
],
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},
{
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"tags": [
"genome"
],
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],
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},
{
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"genome"
],
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],
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},
{
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"description": "European clinical trial database.",
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"clinical-trial"
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"Clinical"
],
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},
{
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"tags": [
"genome"
],
"tasks": [],
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],
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},
{
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"genome"
],
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"Genomics"
],
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},
{
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"tags": [
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],
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],
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},
{
"id": "genomics_of_drug_sensitivity_in_cancer_gdsc",
"name": "Genomics of Drug Sensitivity in Cancer (GDSC)",
"type": "database",
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"description": "Drug sensitivity for ~1000 human cancer cell lines and hundreds of compounds.",
"tags": [
"benchmarks-and-datasets",
"drug-cell-line-response",
"interaction"
],
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],
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"genomics"
],
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"entities": [
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"drug",
"gene"
],
"last_checked": "2026-08-08",
"metadata_sources": [
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]
},
{
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"description": "Genome Aggregation Database; genetic variation from large-scale sequencing projects.",
"tags": [
"genome"
],
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"Genomics"
],
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},
{
"id": "hetionet",
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"type": "database",
"url": "https://github.com/hetio/hetionet",
"description": "Heterogeneous network integrating genes, diseases, drugs, pathways, and more.",
"tags": [
"interaction",
"knowledge-graph"
],
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"Knowledge Graph"
],
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},
{
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"url": "http://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/",
"description": "Human protein-protein interaction database.",
"tags": [
"interaction",
"protein-protein-interaction"
],
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"Protein"
],
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},
{
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"description": "Comprehensive database of small molecule metabolites found in the human body.",
"tags": [
"compound"
],
"tasks": [],
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"Small Molecule"
],
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},
{
"id": "human_cell_atlas",
"name": "Human Cell Atlas",
"type": "database",
"url": "https://www.humancellatlas.org/",
"description": "Open global atlas of all cells in the human body.",
"tags": [
"scrna"
],
"tasks": [],
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"Single Cell"
],
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},
{
"id": "human_genome_resources_at_ncbi",
"name": "Human Genome Resources at NCBI",
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"url": "https://www.ncbi.nlm.nih.gov/projects/genome/guide/human/index.shtml",
"description": "Database for genomics, proteomics, transcriptomics, and systems biology.",
"tags": [
"genome"
],
"tasks": [],
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"Genomics"
],
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},
{
"id": "human_phenotype_ontology_hpo",
"name": "Human Phenotype Ontology (HPO)",
"type": "database",
"url": "https://hpo.jax.org/",
"description": "Standardized vocabulary of phenotypic abnormalities in human disease, linking genes, variants, and clinical features.",
"tags": [
"disease"
],
"tasks": [],
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"Disease"
],
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},
{
"id": "icd10",
"name": "ICD10",
"type": "database",
"url": "https://icd.who.int/browse10/2019/en",
"description": "International Classification of Diseases, 10th revision.",
"tags": [
"clinical-trial"
],
"tasks": [],
"modalities": [
"Clinical"
],
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},
{
"id": "intact",
"name": "IntAct",
"type": "database",
"url": "https://www.ebi.ac.uk/intact/home",
"description": "Open-source molecular interaction database and analysis system from EMBL-EBI.",
"tags": [
"interaction",
"protein-protein-interaction"
],
"tasks": [],
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"Protein"
],
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},
{
"id": "interpro",
"name": "InterPro",
"type": "database",
"url": "https://www.ebi.ac.uk/interpro/",
"description": "Protein families, domains, and functional sites database integrating 14 member databases including Pfam and PROSITE.",
"tags": [
"protein"
],
"tasks": [],
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"Protein"
],
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},
{
"id": "jaspar",
"name": "JASPAR",
"type": "database",
"url": "http://jaspar.genereg.net/",
"description": "Database of transcription factor binding profiles.",
"tags": [
"genome"
],
"tasks": [],
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"Genomics"
],
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"api": false
},
{
"id": "kegg_compound",
"name": "KEGG COMPOUND",
"type": "database",
"url": "https://www.genome.jp/kegg/compound/",
"description": "Collection of small molecules and biopolymers.",
"tags": [
"compound"
],
"tasks": [],
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"Small Molecule"
],
"organism": [],
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},
{
"id": "kegg_drug",
"name": "KEGG DRUG",
"type": "database",
"url": "https://www.genome.jp/kegg/drug/",
"description": "Comprehensive, approved drug information.",
"tags": [
"disease"
],
"tasks": [],
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"Disease"
],
"organism": [],
"api": false
},
{
"id": "kegg_pathway",
"name": "KEGG PATHWAY",
"type": "database",
"url": "https://www.genome.jp/kegg/pathway.html",
"description": "Collection of pathway maps.",
"tags": [
"pathway"
],
"tasks": [],
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"Pathway"
],
"organism": [],
"api": false
},
{
"id": "kinase_inhibitor_bioactivity_data_kiba",
"name": "Kinase Inhibitor Bioactivity Data (KIBA)",
"type": "database",
"url": "https://janeliascicomp.github.io/KIBA/",
"description": "Integrated bioactivity scores for kinase inhibitors combining Ki, Kd, and IC50 measurements.",
"tags": [
"chemical-protein-interaction",
"interaction"
],
"tasks": [],
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"Protein",
"Small Molecule"
],
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},
{
"id": "lipid_maps",
"name": "LIPID MAPS",
"type": "database",
"url": "https://www.lipidmaps.org/databases/lmsd/overview",
"description": "Database of lipids.",
"tags": [
"compound"
],
"tasks": [],
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"Small Molecule"
],
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},
{
"id": "massbank",
"name": "MassBank",
"type": "database",
"url": "http://www.massbank.jp/",
"description": "Open source databases and tools for mass spectrometry reference spectra.",
"tags": [
"mass-spectra"
],
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"modalities": [
"Mass Spectra"
],
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"api": false
},
{
"id": "mgnify",
"name": "MGnify",
"type": "database",
"url": "https://www.ebi.ac.uk/metagenomics/",
"description": "Resource for metagenomic and metatranscriptomic data.",
"tags": [
"genome"
],
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],
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},
{
"id": "mimic_iv",
"name": "MIMIC-IV",
"type": "database",
"url": "https://mimic.mit.edu/",
"description": "Freely accessible critical care database.",
"tags": [
"clinical-trial"
],
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"Clinical"
],
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},
{
"id": "mirbase",
"name": "miRBase",
"type": "database",
"url": "https://www.mirbase.org/",
"description": "Reference repository for microRNA gene annotations, sequences, and experimentally validated targets.",
"tags": [
"gene-regulatory-network",
"interaction"
],
"tasks": [],
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],
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},
{
"id": "mona_massbank_of_north_america",
"name": "MoNA MassBank of North America",
"type": "database",
"url": "https://mona.fiehnlab.ucdavis.edu/",
"description": "Meta-database of metabolite mass spectra, metadata, and associated compounds.",
"tags": [
"mass-spectra"
],
"tasks": [],
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"Mass Spectra"
],
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},
{
"id": "msigdb_molecular_signatures_database",
"name": "MSigDB (Molecular Signatures Database)",
"type": "database",
"url": "https://www.gsea-msigdb.org/gsea/msigdb",
"description": "Curated gene sets derived from pathways and biological processes.",
"tags": [
"pathway"
],
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],
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"api": false
},
{
"id": "nci60",
"name": "NCI60",
"type": "database",
"url": "https://dtp.cancer.gov/discovery_development/nci-60/",
"description": "Focuses on 60 cancer cell lines and many drugs.",
"tags": [
"benchmarks-and-datasets",
"drug-cell-line-response",
"interaction"
],
"tasks": [],
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"Gene Expression",
"Small Molecule"
],
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},
{
"id": "nextprot",
"name": "NeXtProt",
"type": "database",
"url": "https://www.nextprot.org/",
"description": "Expert knowledge base on human proteins with deep functional annotation, complementary to UniProt.",
"tags": [
"protein"
],
"tasks": [],
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],
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},
{
"id": "oadb_observed_antibody_space_database",
"name": "OADB (Observed Antibody Space Database)",
"type": "database",
"url": "http://opig.stats.ox.ac.uk/webapps/oas/",
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{
"id": "scipenn",
"name": "sciPENN",
"type": "toolkit",
"url": "https://github.com/jlakkis/sciPENN",
"description": "RNN-based method for simultaneous protein expression prediction, uncertainty estimation, and cell-type label transfer from CITE-seq and scRNA-seq data.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "scvelo",
"name": "scVelo",
"type": "toolkit",
"url": "https://github.com/theislab/scvelo",
"description": "RNA velocity estimation for single-cell transcriptomics, inferring the direction and speed of cell differentiation.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "scvi_tools",
"name": "scvi-tools",
"type": "toolkit",
"url": "https://scvi-tools.org/",
"description": "Probabilistic models for single-cell omics data analysis.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "seqbench",
"name": "SeqBench",
"type": "toolkit",
"url": "https://seqbench.com/",
"description": "Web-based molecular biology sequence workbench for primer design, cloning simulation (Gibson, Golden Gate, restriction digest), CRISPR guide RNA design, and sequence analysis, with a public REST API, OpenAPI 3.1 spec, and MCP server.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "seurat",
"name": "Seurat",
"type": "toolkit",
"url": "https://satijalab.org/seurat/",
"description": "R library for scRNA-seq analysis.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "squidpy",
"name": "Squidpy",
"type": "toolkit",
"url": "https://squidpy.readthedocs.io/",
"description": "Python library for spatial single-cell analysis.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "stagate",
"name": "STAGATE",
"type": "toolkit",
"url": "https://github.com/RucDongLab/STAGATE",
"description": "Adaptive graph attention auto-encoder for spatial domain identification in spatial transcriptomics.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "star",
"name": "STAR",
"type": "toolkit",
"url": "https://github.com/alexdobin/STAR",
"description": "Ultrafast universal RNA-seq aligner with support for spliced alignment and single-cell quantification via STARsolo.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
},
{
"id": "tigon",
"name": "TIGON",
"type": "toolkit",
"url": "https://github.com/yutongo/TIGON",
"description": "Neural optimal transport method for reconstructing growth and dynamic trajectories from single-cell transcriptomics.",
"tags": [
"preprocessing-tools"
],
"tasks": [
"Preprocessing"
],
"modalities": [],
"organism": [],
"api": false
}
]
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