Cargando…
HIV drug resistance prediction with weighted categorical kernel functions
BACKGROUND: Antiretroviral drugs are a very effective therapy against HIV infection. However, the high mutation rate of HIV permits the emergence of variants that can be resistant to the drug treatment. Predicting drug resistance to previously unobserved variants is therefore very important for an o...
Autores principales: | Ramon, Elies, Belanche-Muñoz, Lluís, Pérez-Enciso, Miguel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668108/ https://www.ncbi.nlm.nih.gov/pubmed/31362714 http://dx.doi.org/10.1186/s12859-019-2991-2 |
Ejemplares similares
-
kernInt: A Kernel Framework for Integrating Supervised and Unsupervised Analyses in Spatio-Temporal Metagenomic Datasets
por: Ramon, Elies, et al.
Publicado: (2021) -
Analysis of Kernel Matrices via the von Neumann Entropy and Its Relation to RVM Performances
por: Belanche-Muñoz, Lluís A., et al.
Publicado: (2023) -
A Novel Boolean Kernels Family for Categorical Data †
por: Polato, Mirko, et al.
Publicado: (2018) -
Bio-kernel Self-organizing Map for HIV Drug Resistance Classification
por: Yang, Zheng Rong, et al.
Publicado: (2005) -
Weighted kernels improve multi-environment genomic prediction
por: Hu, Xiaowei, et al.
Publicado: (2022)