Bionty: Curate metadata using ontologies

• Look up records with auto-completion.

• Map & curate metadata.

• Manage public & custom ontologies and their versions.

To query, collaborate on, and persistently store knowledge & data, consider Bionty’s SQL interface with LaminDB - open-source data lake for biology.

Out-of-the-box ontologies

• Gene: Ensembl, NCBI Gene, HGNC, MGI

• Protein: Uniprot

• Species: NCBI Taxonomy, Ensembl Species

• CellLine: Cell Line Ontology

• CellType: Cell Ontology

• CellMarker: CellMarker

• Tissue: Uberon

• Disease: Mondo, Human Disease

• Phenotype: Human Phenotype

• Pathway: Pathway Ontology

• Readout: Experimental Factor Ontology

Check out versions.yaml for details.

Installation

Bionty is a Python package available for

pip install bionty

Import

In your python script, import Bionty as:

import bionty as bt

Look up ontology terms with autocompletion

gene = bt.Gene()
gene.lookup.LNMA

See Look up records of species, gene, protein, cell marker for more.

Curate metadata

import pandas as pd

# Create an example Pandas DataFrame of various cell types.
df = pd.DataFrame(
    index=[
        "placental epithelial cell",
        "capillary",
        "This cell type does not exist",
    ]
)

# The DataFrame can either be curated by ontology ID (id="ontology_id")
# or by ontology term names (id="name").
curated_df = bt.CellType(id="name").curate(df)

# ✅ 2 terms (66.7%) are mapped.
# 🔶 1 terms (33.3%) are not mapped.

See Curate entity identifiers for more.

Access ontology databases and versions

# Display all managed versions
bt.display_available_versions()

# Access to the Mondo ontology
disease = bt.Disease(database="mondo")

# Access to the Human Disease ontology
disease = bt.Disease(database="doid", version="2023-01-30")

Didn’t see your favorite database or version? See how to Extend Bionty.