BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. Daza, D., Alivanistos, D., Mitra, P., Pijnenburg, T., Cochez, M., & Groth, P. Journal of Biomedical Semantics, 14(1):20, December, 2023. ![BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Knowledge graphs (KGs) are an important tool for representing complex relationships between entities in the biomedical domain. Several methods have been proposed for learning embeddings that can be used to predict new links in such graphs. Some methods ignore valuable attribute data associated with entities in biomedical KGs, such as protein sequences, or molecular graphs. Other works incorporate such data, but assume that entities can be represented with the same data modality. This is not always the case for biomedical KGs, where entities exhibit heterogeneous modalities that are central to their representation in the subject domain.
@article{daza_bioblp_2023,
title = {{BioBLP}: a modular framework for learning on multimodal biomedical knowledge graphs},
volume = {14},
issn = {2041-1480},
url = {https://doi.org/10.1186/s13326-023-00301-y},
doi = {10.1186/s13326-023-00301-y},
abstract = {Knowledge graphs (KGs) are an important tool for representing complex relationships between entities in the biomedical domain. Several methods have been proposed for learning embeddings that can be used to predict new links in such graphs. Some methods ignore valuable attribute data associated with entities in biomedical KGs, such as protein sequences, or molecular graphs. Other works incorporate such data, but assume that entities can be represented with the same data modality. This is not always the case for biomedical KGs, where entities exhibit heterogeneous modalities that are central to their representation in the subject domain.},
number = {1},
journal = {Journal of Biomedical Semantics},
author = {Daza, Daniel and Alivanistos, Dimitrios and Mitra, Payal and Pijnenburg, Thom and Cochez, Michael and Groth, Paul},
month = dec,
year = {2023},
pages = {20},
}
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