vemonet/bioregistry
📮 An integrative registry of biological databases, ontologies, and nomenclatures.
Bioregistry
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 https://bioregistry.io.
📥 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 weekly 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 CONTRIBUTING.md.
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 weekly, 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 updateMake 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 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 docs then view by opening
docs/build/html/index.html.
See the instructions to run the tests
Having tox installed is
required to run the tests. Optionally to run all tests you will need to start
the Bioregistry, a Virtuoso endpoint, and a Blazegraph endpoint using
docker compose:
$ docker compose upThe first time you deploy the docker compose stack, you will need to run an
additional command from another terminal, in this repository root folder, to
enable federated query in Virtuoso:
$ docker compose exec virtuoso isql -U dba -P dba exec='GRANT "SPARQL_SELECT_FED" TO "SPARQL";'After cloning the repository and installing the dependencies, the unit tests in
the tests/ folder can be run reproducibly with:
$ toxAdditionally, these tests are automatically re-run with each commit in a
GitHub Action.
💪 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 'ec' == normalize_prefix('ec-code')
assert 'ec' == normalize_prefix('EC_CODE')
# If a prefix is not registered, it gives back `None`
assert normalize_prefix('not a real key') is NoneParsing 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 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")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:
- 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.
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 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
Gyori Lab for Computational Biomedicine at
https://bioregistry.io.
👋 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 README.md:
[](https://github.com/biopragmatics/bioregistry)If your README uses reStructuredText (.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:
📖 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)
Scientific
Data, s41597-022-01807-3
@article{Hoyt2022Bioregistry,
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 = {https://doi.org/10.1038/s41597-022-01807-3},
volume = {9},
year = {2022}
}Talks on the Bioregistry:
- Future Curation in the Bioregistry
(WPCI, December 2022) - The Bioregistry - Governance and Review Team
(WPCI, December 2022) - Development, Maintenance, and Expansion of the Bioregistry
(Sorger Lab Meeting, October 2022) - The Bioregistry, CURIEs, and OBO Community Health
(ICBO 2022 (September)) - Introduction to the Bioregistry
(Sorger Lab Meeting, July 2021)
🎁 Support
The Bioregistry was primarily developed by the
Gyori Lab for Computational Biomedicine at
Northeastern University, which was previously a part of the
Laboratory of Systems Pharmacology
in the Harvard Program in Therapeutic Science (HiTS)
at Harvard Medical School.
💰 Funding
- Chan Zuckerberg Initiative (CZI) 2023-329850
- DARPA Automating Scientific Knowledge Extraction and Modeling (ASKEM)
HR00112220036 - DARPA Young Faculty Award W911NF2010255 (PI: Benjamin M. Gyori).