The optimal metric for viral genome space.

Alignment-free methods Classification Feature integration Natural vector Optimal metric Viral genomes

Journal

Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369

Informations de publication

Date de publication:
Dec 2024
Historique:
received: 28 11 2023
revised: 22 04 2024
accepted: 04 05 2024
medline: 28 5 2024
pubmed: 28 5 2024
entrez: 28 5 2024
Statut: epublish

Résumé

Understanding the structural similarity between genomes is pivotal in classification and phylogenetic analysis. As the number of known genomes rockets, alignment-free methods have gained considerable attention. Among these methods, the natural vector method stands out as it represents sequences as vectors using statistical moments, enabling effective clustering based on families in biological taxonomy. However, determining an optimal metric that combines different elements in natural vectors remains challenging due to the absence of a rigorous theoretical framework for weighting different

Identifiants

pubmed: 38803517
doi: 10.1016/j.csbj.2024.05.005
pii: S2001-0370(24)00151-X
pmc: PMC11128839
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2083-2096

Informations de copyright

© 2024 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

Déclaration de conflit d'intérêts

None.

Auteurs

Hongyu Yu (H)

Department of Mathematical Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.

Stephen S-T Yau (SS)

Department of Mathematical Sciences, Tsinghua University, Beijing, 100084, People's Republic of China.
Beijing Institute of Mathematical Sciences and Applications (Bimsa), Beijing, 101408, People's Republic of China.

Classifications MeSH