A community-driven integrative meta-registry of biological databases, ontologies, and other resources.
More information here.
The Bioregistry can be accessed, searched, and queried through its associated website at https://bioregistry.io.
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.
If you'd like to request a new prefix, please fill out this issue template. It will automatically generate a pull request! Here's a list of all of the open requests for new prefixes.
There are a few other issue templates for certain updates (e.g., update regex, merge two prefixes, etc.) that you can check here. For anything updates that don't have a corresponding template, feel free to leave a freeform issue for us!
If you want to make a direct contribution, feel free to make edits directly to the bioregistry.json file through the GitHub interface.
Things that would be helpful:
- For all entries, add a
["wikidata"]["database"]entry. Many ontologies and databases don't have a property in Wikidata because the process of adding a new property is incredibly cautious. However, anyone can add a database as normal Wikidata item with a Q prefix. One example is UniPathway, whose Wikidata database item is Q85719315. If there's no database item on Wikidata, you can even make one! Note: don't mix this up with a paper describing the resource, Q35631060. If you see there's a paper, you can add it under the["wikidata"]["paper"]key. - Adding
["homepage"]entry for any entry that doesn't have an external reference
A full list of curation to-do's is automatically generated as a web page here. This page also has a more in-depth tutorial on how to contribute.
For more information on contributions, see CONTRIBUTING.md.
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. The tests fail if even a single metadata is out of place, so don't be frightened that this badge is almost always red.
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 updateMake sure that you have valid environment variables or pystow configurations
for BIOPORTAL_API_KEY, FAIRSHARING_LOGIN, and FAIRSHARING_PASSWORD.
The Bioregistry can be installed from PyPI with:
$ pip install bioregistryIt can be installed in development mode for local curation with:
$ git clone https://github.com/biopragmatics/bioregistry.git
$ cd bioregistry
$ pip install --editable .Build the docs locally with tox -e ldocs then view by opening
docs/build/html/index.html.
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 prefies 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 NoneThe 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.
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')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 identifiers.org, 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('https://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI:24867')
assert 'chebi:24867' == curie_from_iri('https://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI:24867')
# OBO Library PURL
assert ('chebi', '24867') == parse_iri('http://purl.obolibrary.org/obo/CHEBI_24867')
assert 'chebi:24867' == curie_from_iri('http://purl.obolibrary.org/obo/CHEBI_24867')
# OLS IRI
assert ('chebi', '24867') == parse_iri('https://www.ebi.ac.uk/ols/ontologies/chebi/terms?iri=http://purl.obolibrary.org/obo/CHEBI_24867')
assert 'chebi:24867' == curie_from_iri('https://www.ebi.ac.uk/ols/ontologies/chebi/terms?iri=http://purl.obolibrary.org/obo/CHEBI_24867')
# Identifiers.org IRIs (with varying usage of HTTP(s) and colon/slash separator
assert ('chebi', '24867') == parse_iri('https://identifiers.org/CHEBI:24867')
assert ('chebi', '24867') == parse_iri('http://identifiers.org/CHEBI:24867')
assert ('chebi', '24867') == parse_iri('https://identifiers.org/CHEBI/24867')
assert ('chebi', '24867') == parse_iri('http://identifiers.org/CHEBI/24867')
# Bioregistry IRI
assert ('chebi', '24867') == parse_iri('https://bioregistry.io/chebi:24867')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("http://braininfo.rprc.washington.edu/centraldirectory.aspx?ID=268")
assert ('neuronames', '268') == parse_iri("https://braininfo.rprc.washington.edu/centraldirectory.aspx?ID=268")You can add to (or override) the default prefix map from the Bioregistry by
passing a dictionary with the prefix_map keyword:
from bioregistry import curie_from_iri, parse_iri
prefix_map = {
"myprefix": "https://example.org/myprefix/"
}
assert ('myprefix', '1234') == parse_iri("https://example.org/myprefix/1234", prefix_map=prefix_map)
assert 'myprefix:24867' == curie_from_iri("https://example.org/myprefix/1234", prefix_map=prefix_map)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:
- Custom prefix map (
custom) - First-party IRI (
default) - Identifiers.org / MIRIAM (
miriam) - Ontology Lookup Service (
ols) - OBO PURL (
obofoundry) - Name-to-Thing (
n2t) - BioPortal (
bioportal)
from bioregistry import get_iri
assert get_iri("chebi", "24867") == 'https://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI:24867'
assert get_iri("chebi:24867") == 'https://www.ebi.ac.uk/chebi/searchId.do?chebiId=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) == 'http://purl.obolibrary.org/obo/CHEBI_24867'
assert get_iri("hgnc:1234", priority=priority) == 'https://bioregistry.io/hgnc:1234' 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": "https://example.org/myprefix/",
"chebi": "https://example.org/chebi/",
}
assert get_iri("chebi:24867", prefix_map=prefix_map) == 'https://example.org/chebi/24867'
assert get_iri("myprefix:1234", prefix_map=prefix_map) == 'https://example.org/myprefix/1234'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": "https://example.org/lipidmaps/"}
priority = ["obofoundry", "custom", "default", "bioregistry"]
assert get_iri("chebi:24867", prefix_map=prefix_map, priority=priority) == \
'http://purl.obolibrary.org/obo/CHEBI_24867'
assert get_iri("lipidmaps:1234", prefix_map=prefix_map, priority=priority) == \
'https://example.org/lipidmaps/1234'Alternatively, there are direct functions for generating IRIs for different registries:
import bioregistry as br
# Bioregistry IRI
assert br.get_bioregistry_iri('chebi', '24867') == 'https://bioregistry.io/chebi:24867'
# Default Provider
assert br.get_default_iri('chebi', '24867') == 'https://www.ebi.ac.uk/chebi/searchId.do?chebiId=CHEBI:24867'
# OBO Library
assert br.get_obofoundry_iri('chebi', '24867') == 'http://purl.obolibrary.org/obo/CHEBI_24867'
# OLS IRI
assert br.get_ols_iri('chebi', '24867') == \
'https://www.ebi.ac.uk/ols/ontologies/chebi/terms?iri=http://purl.obolibrary.org/obo/CHEBI_24867'
# Bioportal IRI
assert br.get_bioportal_iri('chebi', '24867') == \
'https://bioportal.bioontology.org/ontologies/CHEBI/?p=classes&conceptid=http://purl.obolibrary.org/obo/CHEBI_24867'
# Identifiers.org IRI
assert br.get_identifiers_org_iri('chebi', '24867') == 'https://identifiers.org/CHEBI:24867'
# Name-to-Thing IRI
assert br.get_n2t_iri('chebi', '24867') == 'https://n2t.net/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.
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(priority=priority)
# Provide custom remapping that doesn't have prioritization logic
remapping = {"chebi": "CHEBI"}
prefix_map = get_prefix_map(remapping=remapping)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()After installing with the [web] extras, run the resolver CLI with
$ bioregistry webto run a web app that functions like Identifiers.org, but backed by the Bioregistry. A public instance of this app is hosted by the INDRA Lab at https://bioregistry.io.
The code in this repository is licensed under the MIT License.
If you use the Bioregistry in your code, support us by including our badge in your project's README.md:
[](https://github.com/biopragmatics/bioregistry)If you've got README.rst, use this instead:
.. image:: https://img.shields.io/static/v1?label=Powered%20by&message=Bioregistry&color=BA274A&style=flat&logo=image/png;base64,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
:target: https://github.com/biopragmatics/bioregistry
:alt: Powered by the Bioregistry
It looks like this:
Hopefully there will be a paper describing this resource on bioRxiv sometime in 2021! Until then, you can use the Zenodo BibTeX or CSL.
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.
The development of the Bioregistry is funded by the DARPA Young Faculty Award W911NF2010255 (PI: Benjamin M. Gyori).