A novel Vector-Symbolic Architecture for graph encoding and its application to viral pangenome-based species classification

Fabio Cumbo, Kabir Dhillon, Jayadev Joshi, Davide Chicco, Sercan Aygun, Daniel Blankenberg

Open source

DOI
10.1186/s13040-026-00561-1
Published
2026-05-17
Container
BioData Mining
Publisher
Springer Science and Business Media LLC
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

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