mOWL is a library that provides different machine learning methods in which ontologies are used as background knowledge. mOWL is developed mainly in Python, but we have integrated the functionalities of OWLAPI, which is written in Java, for which we use JPype to bind Python with the Java Virtual Machine (JVM).
- JDK version >= 22.x.x
- Python version: 3.9, 3.10, 3.11, 3.12
- Conda version >= 24.x.x
- torch
- gensim >= 4.3.0
- JPype1 == 1.5.1
- pykeen == 1.11.0
- scipy < 1.15.0
pip install mowl-borg
pip install git+https://github.com/bio-ontology-research-group/mowl
- mOWL: Python library for machine learning with biomedical ontologies
- Ontology Embedding: A Survey of Methods, Applications and Resources
- Evaluating Different Methods for Semantic Reasoning Over Ontologies
- Prioritizing genomic variants through neuro-symbolic, knowledge-enhanced learning
mOWL is a project initiated and developed by the Bio-Ontology Research Group from KAUST. Furthermore, mOWL had other collaboration by being part of:
- Biohackathon Japan 2024
- Biohackathon MENA 2023 as project
#20. - Biohackathon Europe 2022 as project
#18. - Biohackathon Europe 2021 as project
#27.
This software library is distributed under the BSD-3-Clause license
Full documentation and API reference can be found in our ReadTheDocs website.
ChangeLog is available in our changelog file and also in the release section.
If you used mOWL in your work, please consider citing this article:
@article{10.1093/bioinformatics/btac811,
author = {Zhapa-Camacho, Fernando and Kulmanov, Maxat and Hoehndorf, Robert},
title = "{mOWL: Python library for machine learning with biomedical ontologies}",
journal = {Bioinformatics},
year = {2022},
month = {12},
issn = {1367-4803},
doi = {10.1093/bioinformatics/btac811},
url = {https://doi.org/10.1093/bioinformatics/btac811},
note = {btac811},
eprint = {https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btac811/48438324/btac811.pdf},
}