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Integrated registry of biological databases and nomenclatures

Project description


Tests PyPI PyPI - Python Version PyPI - License Documentation Status DOI Code style: black Contributor Covenant

A community-driven integrative meta-registry of life science databases, ontologies, and other resources.
More information here.

The Bioregistry can be accessed, searched, and queried through its associated website at

📥 Download

The underlying data of the Bioregistry can be downloaded (or edited) directly from here. Several exports to YAML, TSV, and RDF, including consensus views over the registry, are built on a nightly basis and can be downloaded via the exports/ directory.

The manually curated portions of these data are available under the CC0 1.0 Universal License. Aggregated data are redistributed under their original licenses.

🙏 Contributing

Contributions are both welcomed and encouraged. Contribution guidelines for new prefix requests, record edits, record removals, and code updates are available in

The most simple contribution is to submit an issue:

  • Submit a new prefix using the issue template. A new pull request will be generated automatically for you.
  • Update an existing record using one of the existing issue templates (e.g., for updating a record's regular expression, merging two prefixes).
  • For any updates that don't have a corresponding template, feel free to start with a blank issue.

If you want to make a direct contribution, feel free to make edits directly to the bioregistry.json file either through the GitHub interface or locally by forking the repository.

If you want to make a contribution but don't know where to start, you can check this list of curation To-Do's that's automatically generated daily, including more detailed information on how to contribute.

⚖️ Governance

The Bioregistry is maintained by a Review Team and Core Development team whose memberships and duties are described in the Project Governance.

🧹 Maintenance

🫀 Health Report

The Bioregistry runs some automated tests weekly to check that various metadata haven't gone stale. For example, it checks that the homepages are still available and that each provider URL is still able to resolve.

It has a dedicated dashboard that is not part of the main Bioregistry site.

♻️ Update

The database is automatically updated daily thanks to scheduled workflows in GitHub Actions. The workflow's configuration can be found here and the last run can be seen here. Further, a changelog can be recapitulated from the commits of the GitHub Actions bot.

If you want to manually update the database, run the following:

$ tox -e update

Make sure that you have valid environment variables or pystow configurations for BIOPORTAL_API_KEY, ECOPORTAL_API_KEY, AGROPORTAL_API_KEY, FAIRSHARING_LOGIN, and FAIRSHARING_PASSWORD.

🚀 Installation

The Bioregistry can be installed from PyPI with:

$ pip install bioregistry

It can be installed in development mode for local curation with:

$ git clone
$ cd bioregistry
$ pip install --editable .

Build the docs locally with tox -e ldocs then view by opening docs/build/html/index.html.

💪 Usage

Normalizing Prefixes

The Bioregistry can be used to normalize prefixes across MIRIAM and all the (very plentiful) variants that pop up in ontologies in OBO Foundry and the OLS with the normalize_prefix() function.

from bioregistry import normalize_prefix

# Doesn't affect canonical prefixes
assert 'ncbitaxon' == normalize_prefix('ncbitaxon')

# This works for uppercased prefixes, like:
assert 'chebi' == normalize_prefix("CHEBI")

# This works for mixed case prefixes like
assert 'fbbt' == normalize_prefix("FBbt")

# This works for synonym prefixes, like:
assert 'ncbitaxon' == normalize_prefix('taxonomy')

# This works for common mistaken prefixes, like:
assert 'pubchem.compound' == normalize_prefix('pubchem')

# This works for prefixes that are often written many ways, like:
assert 'eccode' == normalize_prefix('ec-code')
assert 'eccode' == normalize_prefix('EC_CODE')

# If a prefix is not registered, it gives back `None`
assert normalize_prefix('not a real key') is None

Parsing CURIEs

The Bioregistry supports parsing a CURIE into a pair of normalized prefix and identifier using the parse_curie() function:

from bioregistry import parse_curie

# Obvious for canonical CURIEs
assert ('chebi', '1234') == parse_curie('chebi:1234')

# Normalize mixed case prefixes
assert ('fbbt', '00007294') == parse_curie('FBbt:00007294')

# Normalize common mistaken prefixes
assert ('pubchem.compound', '1234') == parse_curie('pubchem:1234')

# Remove the redundant prefix and normalize
assert ('go', '1234') == parse_curie('GO:GO:1234')

This will also apply the same normalization rules for prefixes from the previous section on normalizing prefixes for the remaining examples.

Normalizing CURIEs

The Bioregistry supports converting a CURIE to a canonical CURIE by normalizing the prefix and removing redundant namespaces embedded in LUIs with the normalize_curie() function.

from bioregistry import normalize_curie

# Idempotent to canonical CURIEs
assert 'chebi:1234' == normalize_curie('chebi:1234')

# Normalize common mistaken prefixes
assert 'pubchem.compound:1234' == normalize_curie('pubchem:1234')

# Normalize mixed case prefixes
assert 'fbbt:1234' == normalize_curie('FBbt:1234')

# Remove the redundant prefix and normalize
assert 'go:1234' == normalize_curie('GO:GO:1234')

Parsing IRIs

The Bioregistry can be used to parse CURIEs from IRIs due to its vast registry of provider URL strings and additional programmatic logic implemented with Python. It can parse OBO Library PURLs, IRIs from the OLS and, IRIs from the Bioregistry website, and any other IRIs from well-formed providers registered in the Bioregistry. The parse_iri() function gets a pre-parsed CURIE, while the curie_from_iri() function makes a canonical CURIE from the pre-parsed CURIE.

from bioregistry import curie_from_iri, parse_iri

# First-party IRI
assert ('chebi', '24867') == parse_iri('')
assert 'chebi:24867' == curie_from_iri('')

# OBO Library PURL
assert ('chebi', '24867') == parse_iri('')
assert 'chebi:24867' == curie_from_iri('')

assert ('chebi', '24867') == parse_iri('')
assert 'chebi:24867' == curie_from_iri('')

# IRIs (with varying usage of HTTP(s) and colon/slash separator
assert ('chebi', '24867') == parse_iri('')
assert ('chebi', '24867') == parse_iri('')
assert ('chebi', '24867') == parse_iri('')
assert ('chebi', '24867') == parse_iri('')

# Bioregistry IRI
assert ('chebi', '24867') == parse_iri('')

In general, the Bioregistry knows how to parse both the http and https variants of any given URI:

from bioregistry import parse_iri

assert ('neuronames', '268') == parse_iri("")
assert ('neuronames', '268') == parse_iri("")

Generating IRIs

You can generate an IRI from either a CURIE or a pre-parsed CURIE (i.e., a 2-tuple of a prefix and identifier) with the get_iri() function. By default, it uses the following priorities:

  1. Custom prefix map (custom)
  2. First-party IRI (default)
  3. / MIRIAM (miriam)
  4. Ontology Lookup Service (ols)
  5. OBO PURL (obofoundry)
  6. Name-to-Thing (n2t)
  7. BioPortal (bioportal)
from bioregistry import get_iri

assert get_iri("chebi", "24867") == ''
assert get_iri("chebi:24867") == ''

It's possible to change the default priority list by passing an alternate sequence of metaprefixes to the priority keyword (see above). For example, if you're working with OBO ontologies, you might want to make OBO PURLs the highest priority and when OBO PURLs can't be generated, default to something else:

from bioregistry import get_iri

priority = ["obofoundry", "default", "miriam", "ols", "n2t", "bioportal"]
assert get_iri("chebi:24867", priority=priority) == ''
assert get_iri("hgnc:1234", priority=priority) == '' 

Even deeper, you can add (or override) any of the Bioregistry's default prefix map with the prefix_map keyword:

from bioregistry import get_iri

prefix_map = {
   "myprefix": "",
   "chebi": "",
assert get_iri("chebi:24867", prefix_map=prefix_map) == ''
assert get_iri("myprefix:1234", prefix_map=prefix_map) == ''

A custom prefix map can be supplied in combination with a priority list, using the "custom" key for changing the priority of the custom prefix map.

from bioregistry import get_iri

prefix_map = {"lipidmaps": ""}
priority = ["obofoundry", "custom", "default", "bioregistry"]
assert get_iri("chebi:24867", prefix_map=prefix_map, priority=priority) == \
assert get_iri("lipidmaps:1234", prefix_map=prefix_map, priority=priority) == \

Alternatively, there are direct functions for generating IRIs for different registries:

import bioregistry as br

# Bioregistry IRI
assert br.get_bioregistry_iri('chebi', '24867') == ''

# Default Provider
assert br.get_default_iri('chebi', '24867') == ''

# OBO Library
assert br.get_obofoundry_iri('chebi', '24867') == ''

assert br.get_ols_iri('chebi', '24867') ==

# Bioportal IRI
assert br.get_bioportal_iri('chebi', '24867') == \

assert br.get_identifiers_org_iri('chebi', '24867') == ''

# Name-to-Thing IRI
assert br.get_n2t_iri('chebi', '24867') == ''

Each of these functions could also return None if there isn't a provider available or if the prefix can't be mapped to the various resources.

Prefix Map

The Bioregistry can be used to generate prefix maps with various flavors depending on your context. Prioritization works the same way as when generating IRIs.

from bioregistry import get_prefix_map

# Standard
prefix_map = get_prefix_map()

# Prioritize OBO prefixes over bioregistry
priority = ["obofoundry", "default", "miriam", "ols", "n2t", "bioportal"]
prefix_map = get_prefix_map(uri_prefix_priority=priority)

# Provide custom remapping that doesn't have prioritization logic
remapping = {"chebi": "CHEBI"}
prefix_map = get_prefix_map(remapping=remapping)

Getting Metadata

The pattern for an entry in the Bioregistry can be looked up quickly with get_pattern() if it exists. It prefers the custom curated, then MIRIAM, then Wikidata pattern.

import bioregistry

assert '^GO:\\d{7}$' == bioregistry.get_pattern('go')

Entries in the Bioregistry can be checked for deprecation with the is_deprecated() function. MIRIAM and OBO Foundry don't often agree - OBO Foundry takes precedence since it seems to be updated more often.

import bioregistry

assert bioregistry.is_deprecated('nmr')
assert not bioregistry.is_deprecated('efo')

Entries in the Bioregistry can be looked up with the get_resource() function.

import bioregistry

entry = bioregistry.get_resource('taxonomy')
# there are lots of mysteries to discover in this dictionary!

The full Bioregistry can be read in a Python project using:

import bioregistry

registry = bioregistry.read_registry()

🕸️ Resolver App

After installation with the [web] extras, the Bioregistry web application can be run with the following code:

$ python -m pip install bioregistry[web]
$ bioregistry web

to run a web app that functions like, but backed by the Bioregistry. A public instance of this app is hosted by the INDRA Lab at

👋 Attribution

⚖️ License

The code in this repository is licensed under the MIT License.

📛 Badge

If you use the Bioregistry in your code, support us by including our badge in your project's

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    :alt: Powered by the Bioregistry

It looks like this: Powered by the Bioregistry

📖 Citation

Unifying the identification of biomedical entities with the Bioregistry
Hoyt, C. T., Balk, M., Callahan, T. J., Domingo-Fernandez, D., Haendel, M. A., Hegde, H. B., Himmelstein, D. S., Karis, K., Kunze, J., Lubiana, T., Matentzoglu, N., McMurry, J., Moxon, S., Mungall, C. J., Rutz, A., Unni, D. R., Willighagen, E., Winston, D., and Gyori, B. M. (2022)
Nature Scientific Data, s41597-022-01807-3

    author = {Hoyt, Charles Tapley and Balk, Meghan and Callahan, Tiffany J and Domingo-Fern{\'{a}}ndez, Daniel and Haendel, Melissa A and Hegde, Harshad B and Himmelstein, Daniel S and Karis, Klas and Kunze, John and Lubiana, Tiago and Matentzoglu, Nicolas and McMurry, Julie and Moxon, Sierra and Mungall, Christopher J and Rutz, Adriano and Unni, Deepak R and Willighagen, Egon and Winston, Donald and Gyori, Benjamin M},
    doi = {10.1038/s41597-022-01807-3},
    issn = {2052-4463},
    journal = {Sci. Data},
    number = {1},
    pages = {714},
    title = {{Unifying the identification of biomedical entities with the Bioregistry}},
    url = {},
    volume = {9},
    year = {2022}

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🎁 Support

The Bioregistry was developed by the INDRA Lab, a part of the Laboratory of Systems Pharmacology and the Harvard Program in Therapeutic Science (HiTS) at Harvard Medical School.

💰 Funding

The development of the Bioregistry is funded by the DARPA Young Faculty Award W911NF2010255 (PI: Benjamin M. Gyori).

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