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Home page of a biological database called characterises functional links between proteins[1]

Biological databases are libraries of biological sciences, collected from scientific experiments, published literature, high-throughput experiment technology, and computational analysis.[citation needed] They contain information from research areas including genomics, proteomics, metabolomics, microarray gene expression, and phylogenetics.[2] Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures.

Biological databases can be classified by the kind of data they collect (see below). Broadly, there are molecular databases (for sequences, molecules, etc.), functional databases (for physiology, enzyme activities, phenotypes, ecology etc), taxonomic databases (for species and other taxonomic ranks), images and other media, or specimens (for museum collections etc.)

Databases are important tools in assisting scientists to analyze and explain a host of biological phenomena from the structure of biomolecules and their interaction, to the whole metabolism of organisms and to understanding the evolution of species. This knowledge helps facilitate the fight against diseases, assists in the development of medications, predicting certain genetic diseases and in discovering basic relationships among species in the history of life.

Major Biological Databases

These tables cover a variety of notable biological databses across a wide swath of fields, specialties, data types, and use-cases. Many of these databases are collated in the ELIXIR Core Data Resource list which collects important European data resources critical to life science research.[3]

ELIXIR Core Data Resources[4]
Resource Category Host institution Description[3]
ArrayExpress[5] Transcriptomics EMBL-EBI /

European Nucleotide Archive[5]

Functional genomics data from high-throughput experiments
BacDive[6] Microbiology Leibniz Institute DSMZ Taxonomy, morphology, physiology, and ecology of bacterial and archaeal strains
Bgee[7] Transcriptomics Swiss Institute of Bioinformatics / University of Lausanne[7] Gene expression patterns across multiple animal species for comparative analysis
BioImage Archive[8] Imaging EMBL-EBI[8] Repository of biological images, supporting the deposition and reuse of reference imaging data that underpin published research across the life sciences.
BioStudies[9] Metadata EMBL-EBI[9] Descriptions of biological studies and supplementary data linking to other archives
BRENDA[10] Enzymology Leibniz Institute DSMZ[10] Enzyme and enzyme–ligand information curated from primary literature across all taxa
CATH[11] Protein Structure University College London[11] Hierarchical domain classification of protein structures from the PDB
Cellosaurus[12] Cells Swiss Institute of Bioinformatics[12] Knowledge resource describing cell lines used in biomedical research
ChEBI[13] Biochemistry EMBL-EBI[13] Dictionary of small molecular entities of biological interest
ChEMBL[14] Biochemistry EMBL-EBI[14] Bioactive drug-like small molecules with 2-D structures. calculated properties, and bioactivities
EGA[15] Genome EMBL-EBI / CRG[15] Personally identifiable genetic and phenotypic data from biomedical research
EMDB[16] Biochemical Structure EMBL-EBI[16] Cryo-EM maps and tomograms of macromolecular complexes and subcellular structures
ENA[17] Sequence EMBL-EBI[17] Nucleotide sequencing data, sequence assemblies, and functional annotation
Ensembl[18] Genome EMBL-EBI[18] Genome browser for vertebrate genomes supporting comparative and regulatory genomics
Ensembl Genomes[19] Genome EMBL-EBI[19] Comparative analysis and visualisation for non-vertebrate genomes
Europe PMC[20] Literature EMBL-EBI[20] Life-sciences articles, books, patents, and clinical guidelines
GWAS Catalog[21] Variation EMBL-EBI / NHGRI[22] Curated collection of human genome-wide association studies
HGNC[23] Nomenclature University of Cambridge / EMBL-EBI[23] Approved symbols, names, and families for human genes
Human Protein Atlas[24] Proteomics KTH Royal Institute of Technology / Karolinska Institute / Uppsala Universitet[24] Human proteome mapped across cells, tissues, and organs via multi-omics and imaging
IntAct[25] / MINT[26] (IMEx) Interactions EMBL-EBI [25] Experimentally verified protein–protein and molecular interaction data
InterPro[27] Protein EMBL-EBI[27] Protein families, domains, and functional sites integrated from member databases
JASPAR[28] Regulation University of Oslo[28] Curated, non-redundant transcription factor binding profiles
MGnify[29] Metagenomics EMBL-EBI[29] Assembly, analysis, and archiving of microbiome-derived nucleic-acid sequences
LIPID MAPS[30] Lipidomics Cardiff University / UCSD / Babraham Institute / Swansea University / University of Edinburgh[30] Lipid structures, properties, and biological functions
LPSN[31] Nomenclature Leibniz Institute DSMZ[31] Authoritative nomenclature of prokaryotes
Orphadata Science[32] Disease Inserm / French Ministry of Health[32] Computable dataset of rare diseases and orphan drugs
OMA[33] Orthology Swiss Institute of Bioinformatics / University of Lausanne[33] Inferred orthologs among complete genomes
OrthoDB[34] Orthology Swiss Institute of Bioinformatics / University of Geneva[34] Orthologous protein-coding genes across a wide range of species
PDBe[35] Structure EMBL-EBI[35] Biological macromolecular structures
PomBase[36] Genome University of Cambridge / University College London / Babraham Institute[36] Structural and functional annotation for the fission yeast Schizosaccharomyces pombe
PRIDE[37] Proteomics EMBL-EBI[37] Mass-spectrometry-based proteomics identifications, quantifications, and spectra
Reactome[38] Pathways EMBL-EBI / OICR / NYU[38] Manually curated and peer-reviewed biological pathways
Rhea[39] Chemistry Swiss Institute of Bioinformatics[39] Expert-curated chemical and transport reactions of biological interest
SILVA[40] Sequence Leibniz Institute DSMZ[40] Comprehensive, quality-checked, and regularly updated datasets of aligned small and large subunit ribosomal RNA sequences for all three domains of life (Bacteria, Archaea and Eukarya)
STRING[41] Interactions Swiss Institute of Bioinformatics / Novo Nordisk Foundation Center Protein Research / EMBL-EBI[41] Known and predicted protein–protein interactions
SWISS-MODEL[42] Structure Swiss Institute of Bioinformatics / University of Basel[42] Automated protein structure homology modelling
UniProt[43] Protein EMBL-EBI / SIB / PIR[43] Comprehensive protein sequence and functional annotation
VEuPathDB[44] Pathogens University of Pennsylvania / University of Georgia / University of Liverpool[44] Genomic and functional data for eukaryotic pathogens and invertebrate disease vectors

Access

Most biological databases are available through web sites that organise data such that users can browse through the data online. In addition the underlying data is usually available for download in a variety of formats. Biological data comes in many formats. These formats include text, sequence data, protein structure and links. Each of these can be found from certain sources, for example:[citation needed]

  • Text formats are provided by PubMed and OMIM.
  • Sequence data is provided by GenBank, in terms of DNA, and UniProt, in terms of protein.
  • Protein structures are provided by PDB, SCOP, and CATH.

Problems and challenges

Biological knowledge is distributed among countless databases. This sometimes makes it difficult to ensure the consistency of information, e.g. when different names are used for the same species or different data formats. As a consequence, inter-operability is a constant challenge for information exchange. For instance, if a DNA sequence database stores the DNA sequence along the name of a species, a name change of that species may break the links to other databases which may use a different name. Integrative bioinformatics is one field attempting to tackle this problem by providing unified access. One solution is how biological databases cross-reference to other databases with accession numbers to link their related knowledge together (e.g. so that the accession number stays the same even if a species name changes). Redundancy is another problem, as many databases must store the same information, e.g. protein structure databases also contain the sequence of the proteins they cover, their sequence, and their bibliographic information.

Model-organism databases

Main article: Model organism database

Species-specific databases are available for some species, mainly those that are often used in research (model organisms). For example, EcoCyc is an E. coli database. Other popular model organism databases include Mouse Genome Informatics for the laboratory mouse, Mus musculus, the Rat Genome Database for Rattus, ZFIN for Danio Rerio (zebrafish), PomBase[45] for the fission yeast Schizosaccharomyces pombe, FlyBase for Drosophila, WormBase for the nematodes Caenorhabditis elegans and Caenorhabditis briggsae, and Xenbase for Xenopus tropicalis and Xenopus laevis frogs.

Biodiversity and species databases

Animal groups and their number of species from the Catalogue of Life[46]

Numerous databases attempt to document the diversity of life on earth. A prominent example is the Catalogue of Life, first created in 2001 by Species 2000 and the Integrated Taxonomic Information System.[47] The Catalogue of Life is a collaborative project that aims to document taxonomic categorization of all currently accepted species in the world.[48] The Catalogue of Life provides a consolidated and consistent database for researchers and policymakers to reference. The Catalogue of Life curates up-to-date datasets from other sources such as Conifer Database, ICTV MSL (for viruses), and LepIndex (for butterflies and moths). In total, the Catalogue of Life draws from 165 databases as of May 2022.[49] Operational costs of the Catalogue of Life are paid for by the Global Biodiversity Information Facility, the Illinois Natural History Survey, the Naturalis Biodiversity Center, and the Smithsonian Institution.[50]

Some biological databases also document geographical distribution of different species. Shuang Dai et al. created a new multi-source database to document spatial/geographical distribution of 1,371 bird species in China, as existing databases had been severely lacking in spatial distribution data for many species.[51] Sources for this new database included books, literature, GPS tracking, and online webpage data. The new database displayed taxonomy, distribution, species info, and data sources for each species. After completion of the bird spatial distribution database, it was discovered that 61% of known species in China were found to be distributed in regions beyond where they were previously known.[52]

Medical databases

Foot wounds from WoundsDB[53]

Medical databases are a special case of biomedical data resource and can range from bibliographies, such as PubMed, to image databases for the development of AI based diagnostic software. For instance, one such image database was developed with the goal of aiding in the development of wound monitoring algorithms.[54] Over 188 multi-modal image sets were curated from 79 patient visits, consisting of photographs, thermal images, and 3D mesh depth maps. Wound outlines were manually drawn and added to the photo datasets.[55] The database was made publicly available in the form of a program called WoundsDB, downloadable from the Chronic Wound Database website.

Nucleic Acids Research Database Issue

An important resource for finding biological databases is a special yearly issue of the journal Nucleic Acids Research (NAR). The Database Issue of NAR is freely available, and categorizes many of the public biological databases. A companion database to the issue called the Online Molecular Biology Database Collection lists 1,380 online databases.[56] Other collections of databases exist such as MetaBase and the Bioinformatics Links Collection.[57][58]

See also

References

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  2. ^ Altman RB (March 2004). “Building successful biological databases”. Brief. Bioinformatics. 5 (1): 4–5. doi:10.1093/bib/5.1.4. PMID 15153301.
  3. ^ a b “ELIXIR Core Data Resources | ELIXIR”. elixir-europe.org. Retrieved 2026-04-09.
  4. ^ “Core Data Resources”. ELIXIR. Retrieved 2026-04-08.
  5. ^ a b BioStudies. “BioStudies < The European Bioinformatics Institute < EMBL-EBI”. www.ebi.ac.uk. Retrieved 2026-04-09.
  6. ^ “BacDive | The Bacterial Diversity Metadatabase”. bacdive.dsmz.de. Retrieved 2026-04-09.
  7. ^ a b “Bgee: gene expression data in animals”. Bgee. Retrieved 2026-04-09.
  8. ^ a b EMBL-EBI. “Home < BioImage Archive < EMBL-EBI”. www.ebi.ac.uk. Retrieved 2026-04-09.
  9. ^ a b EMBL-EBI. “Home < BioImage Archive < EMBL-EBI”. www.ebi.ac.uk. Retrieved 2026-04-09.
  10. ^ a b “BRENDA Enzyme Database”. www.brenda-enzymes.org. Retrieved 2026-04-09.
  11. ^ a b “CATH: Protein Structure Classification Database at UCL”. www.cathdb.info. Retrieved 2026-04-09.
  12. ^ a b “Cellosaurus – Cell line encyclopedia”. www.cellosaurus.org. Retrieved 2026-04-09.
  13. ^ a b “ChEBI – Chemical Entities of Biological Interest”. www.ebi.ac.uk. Retrieved 2026-04-09.
  14. ^ a b “ChEMBL – ChEMBL”. www.ebi.ac.uk. Retrieved 2026-04-09.
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  16. ^ a b EMDB. “Electron Microscopy Data Bank”. Electron Microscopy Data Bank. Retrieved 2026-04-09.
  17. ^ a b “ENA Browser”. www.ebi.ac.uk. Retrieved 2026-04-09.
  18. ^ a b “Ensembl genome browser 115”. www.ensembl.org. Retrieved 2026-04-09.
  19. ^ a b “Ensembl Genomes”. ensemblgenomes.org. Retrieved 2026-04-09.
  20. ^ a b “Europe PMC”. europepmc.org. Retrieved 2026-04-09.
  21. ^ “GWAS Catalog”. www.ebi.ac.uk. Retrieved 2026-04-09.
  22. ^ “GWAS Catalog”. www.ebi.ac.uk. Retrieved 2026-04-09.
  23. ^ a b “Home | HUGO Gene Nomenclature Committee”. www.genenames.org. Retrieved 2026-04-09.
  24. ^ a b “The Human Protein Atlas”. www.proteinatlas.org. Retrieved 2026-04-09.
  25. ^ a b “IntAct Portal”. www.ebi.ac.uk. Retrieved 2026-04-09.
  26. ^ “The Molecular INTeraction Database – An ELIXIR Core Resource”. Retrieved 2026-04-09.
  27. ^ a b “InterPro”. www.ebi.ac.uk. Retrieved 2026-04-09.
  28. ^ a b “InterPro”. www.ebi.ac.uk. Retrieved 2026-04-09.
  29. ^ a b “MGnify – EBI”. www.ebi.ac.uk. Retrieved 2026-04-09.
  30. ^ a b Conroy, Matthew J; Andrews, Robert M; Andrews, Simon; Cockayne, Lauren; Dennis, Edward A; Fahy, Eoin; Gaud, Caroline; Griffiths, William J; Jukes, Geoff; Kolchin, Maksim; Mendivelso, Karla; Lopez-Clavijo, Andrea F; Ready, Caroline; Subramaniam, Shankar; O’Donnell, Valerie B (2024-01-05). “LIPID MAPS: update to databases and tools for the lipidomics community”. Nucleic Acids Research. 52 (D1): D1677–D1682. doi:10.1093/nar/gkad896. ISSN 0305-1048. PMC 10767878. PMID 37855672.
  31. ^ a b “LPSN – List of Prokaryotic names with Standing in Nomenclature”. lpsn.dsmz.de. Retrieved 2026-04-09.
  32. ^ a b “Science Orphadata – Orphanet datasets”. sciences.orphadata.com. Retrieved 2026-04-09.
  33. ^ a b “OMA Orthology database”. omabrowser.org. Retrieved 2026-04-09.
  34. ^ a b “OrthoDB | genes orthologs | Zdobnov lab”. www.orthodb.org. Retrieved 2026-04-09.
  35. ^ a b “Homepage | Protein Data Bank in Europe”. www.ebi.ac.uk. Retrieved 2026-04-09.
  36. ^ a b “PomBase”. www.pombase.org. Retrieved 2026-04-09.
  37. ^ a b “PRIDE – PRoteomics IDEntifications Database”. www.ebi.ac.uk. Retrieved 2026-04-09.
  38. ^ a b “Home – Reactome Pathway Database”. reactome.org. Retrieved 2026-04-09.
  39. ^ a b “Rhea – reaction knowledgebase”. www.rhea-db.org. Retrieved 2026-04-09.
  40. ^ a b “SILVA: Silva”. www.arb-silva.de. Retrieved 2026-04-09.
  41. ^ a b “STRING: functional protein association networks”. string-db.org. Retrieved 2026-04-09.
  42. ^ a b “SWISS-MODEL”. swissmodel.expasy.org. Retrieved 2026-04-09.
  43. ^ a b “UniProt”. UniProt. Retrieved 2026-04-09.
  44. ^ a b “VEuPathDB”. veupathdb.org. Retrieved 2026-04-09.
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  46. ^ Catalogue of Life (2001). “Homepage”. Search. Species 2000. Archived from the original on 2022-05-05. Retrieved 2022-05-05.
  47. ^ Jones, Andrew C. (2011). “Identifying and Relating Biological Concepts in the Catalogue of Life”. Journal of Biomedical Semantics. 2 (1): 7. doi:10.1186/2041-1480-2-7. PMC 3245425. PMID 22004596.
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  49. ^ Catalogue of Life (2001). “Source Datasets”. Species 2000. Archived from the original on 2022-05-14. Retrieved 2022-05-05.
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  51. ^ Dai, Shuang (2019). “A Spatialized Digital Database for All Bird Species in China”. Science China Life Sciences. 62 (5): 661–667. doi:10.1007/s11427-018-9419-2. PMID 30900164. S2CID 84845653.
  52. ^ Dai, Shuang (2019). “A Spatialized Digital Database for All Bird Species in China”. Science China Life Sciences. 62 (5): 661–667. doi:10.1007/s11427-018-9419-2. PMID 30900164. S2CID 84845653.
  53. ^ “Chronic Wound Database”. WoundsDB. Silesian University of Technology. 2020. Retrieved 2022-05-05.
  54. ^ Kręcichwost, Michał (2021). “Chronic Wounds Multimodal Image Database”. Computerized Medical Imaging and Graphics. 88 101844. doi:10.1016/j.compmedimag.2020.101844. PMID 33477091. S2CID 231676950.
  55. ^ “Chronic Wound Database”. WoundsDB. Silesian University of Technology. 2020. Retrieved 2022-05-05.
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  57. ^ Bolser DM; Chibon PY; Palopoli N; et al. (January 2012). “MetaBase–the wiki-database of biological databases”. Nucleic Acids Res. 40 (Database issue): D1250–4. doi:10.1093/nar/gkr1099. PMC 3245051. PMID 22139927.
  58. ^ Brazas MD; Yim DS; Yamada JT; Ouellette BF (July 2011). “The 2011 Bioinformatics Links Directory update: more resources, tools and databases and features to empower the bioinformatics community”. Nucleic Acids Res. 39 (Web Server issue): W3–7. doi:10.1093/nar/gkr514. PMC 3125814. PMID 21715385.