ArticleBioinformatics advances2024
Investigating alignment-free machine learning methods for HIV-1 subtype classification.
Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development of a Subsequence Correlation Coefficient Feature Vector Method for High-Resolution HIV-1 Subtype Classification - China, 2004-2022.China CDC weekly · 2026Article
- Machine Learning Application in Enhancing HIV Management and Treatment Outcomes: Revolutionizing HIV Infection.Current HIV research · 2026Review
- Environmental adaptations in metagenomes revealed by deep learning.BMC biology · 2025Article
- Genome language modeling (GLM): a beginner's cheat sheet.Biology methods & protocols · 2025Article
- Craft: a machine learning approach to dengue subtyping.Bioinformatics advances · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Many viruses are organized into taxonomies of subtypes based on their genetic similarities. For human immunodeficiency virus 1 (HIV-1), subtype classification plays a crucial role in infection management. Sequence alignment-based methods for subtype classification are impractical for large datasets because they are costly and time-consuming. Alignment-free methods involve creating numerical representations for genetic sequences and applying statistical or machine learning methods. Despite their high overall accuracy, existing models perform poorly on less common subtypes. Furthermore, there is limited work investigating the impact of sequence vectorization methods, in particular natural language-inspired embedding methods, on HIV-1 subtype classification. Results: We present a comprehensive analysis of sequence vectorization methods across machine learning methods. We report a Availability and implementation: Source code is available at https://www.github.com/kwade4/HIV_Subtypes.
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Registered trials
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