Machine Learning Approaches to Biomarker Discovery in Hemic Neoplasia of Mercenaria mercenaria
Document Type
Presentation
Date of Original Version
3-27-2026
Abstract
Bivalve Transmissible Neoplasia (BTN), also referred to as hemic or disseminated neoplasia (HN or DN), is a clonally transmissible cancer of bivalve hemocytes that poses a critical threat to hard-shell clam, Mercenaria mercenaria, aquaculture, with mortality reaching 80–90% in affected bivalve populations (Barber, 2004; Villalba et al., 2004; Weinandt et al., 2024,Smolowitz et al., 2025). Current diagnostic methods such as hemolymph smears and histology are still only able to detect advanced stages, and this allows undetected carriers to contribute to this transmission, delaying implementation of management strategies (House and Elston, 2006; Giersch et al, 2022). This study will apply a machine learning approach to identify early molecular indicators of BTN derived from single-cell RNA sequencing data of normal and neoplastic clams and will further the understanding of the possible mechanisms of neoplastic progression and the drive development of more high-throughput diagnostic tools.
Recommended Citation
Paz, Alberto, "Machine Learning Approaches to Biomarker Discovery in Hemic Neoplasia of Mercenaria mercenaria" (2026). Oral Presentations. Paper 14.
https://digitalcommons.uri.edu/gradcon2026-presentations/14