A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification
- DOI
- 10.1186/s13040-026-00561-1
- Published
- 2026-05-17
- Container
- BioData Mining
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s13040-026-00561-1,
title = {A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification},
author = {Fabio Cumbo and Kabir Dhillon and Jayadev Joshi and Davide Chicco and Sercan Aygun and Daniel Blankenberg},
year = {2026},
journal = {BioData Mining},
doi = {10.1186/s13040-026-00561-1},
url = {https://doi.org/10.1186/s13040-026-00561-1}
}RIS
TY - JOUR TI - A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification AU - Fabio Cumbo AU - Kabir Dhillon AU - Jayadev Joshi AU - Davide Chicco AU - Sercan Aygun AU - Daniel Blankenberg PY - 2026 JO - BioData Mining DO - 10.1186/s13040-026-00561-1 UR - https://doi.org/10.1186/s13040-026-00561-1 ER -
APA
Cumbo, F., Dhillon, K., Joshi, J., Chicco, D., Aygun, S., & Blankenberg, D. (2026). A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification. BioData Mining. https://doi.org/10.1186/s13040-026-00561-1
Source records
- crossref · retrieved 2026-09-26T06:51:46.934Z