Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis
Collectively, these findings highlight the XOR model's ability to uncover meaningful biological associations and higher-order epistasis derived from lower-order network topologies. The introduction of community-based enrichment analysis and motif-based epistatic discovery emphasize network science as a critical approach for advancing epistasis research and understanding complex genetic architectures.
Authors
- Attri Ghosh
- Jason H. Moore (ORCID: https://orcid.org/0000-0002-5015-1099)
- Philip J. Freda (ORCID: https://orcid.org/0000-0001-8658-9802)
- Zhendong Sha (ORCID: https://orcid.org/0000-0002-7694-1099)
- Nicholas Matsumoto (ORCID: https://orcid.org/0000-0002-3280-9678)
- Ting Hu (ORCID: https://orcid.org/0000-0001-6382-0602)
- Priyanka Bhandary (ORCID: https://orcid.org/0000-0002-6962-9638)
Institutions
- Cedars-Sinai Medical Center (US)
- Queen's University (CA)
Publication Details
- Journal
- BioData Mining
- Published
- 2024-12-28
- DOI
- https://doi.org/10.1186/s13040-024-00413-w
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.23
Funders
- Alliance de recherche numérique du Canada
- National Institutes of Health