Craft: A Machine Learning Approach to Dengue Subtyping.

• Tác giả: Cheryl Baxter, Tulio de Oliveira, Marcel Dunaiski, Houriiyah Tegally, Daniel J van Zyl, Joicymara S Xavier
• Ngôn ngữ: eng
• Ký hiệu phân loại: 623.8256 Nautical engineering and seamanship
• Thông tin xuất bản: United States : bioRxiv : the preprint server for biology , 2025
• Bộ sưu tập: NCBI
• ID: 738660
• Chủ đề: 1. Machine Shops—automation— Shock Absorbers; 2. Machine Shops—automation

Tóm tắt

MOTIVATION: The dengue virus poses a major global health threat, with nearly 390 million infections annually. A recently proposed hierarchical dengue nomenclature system enhances spatial resolution by defining major and minor lineages within genotypes, aiding efforts to track viral evolution. While current subtyping tools - Genome Detective, GLUE, and NextClade - rely on computationally intensive sequence alignment and phylogenetic inference, machine learning presents a promising alternative for achieving accurate and rapid classification. RESULTS: We present Craft (