Cargando…
Quantifying selection in high-throughput Immunoglobulin sequencing data sets
High-throughput immunoglobulin sequencing promises new insights into the somatic hypermutation and antigen-driven selection processes that underlie B-cell affinity maturation and adaptive immunity. The ability to estimate positive and negative selection from these sequence data has broad application...
Autores principales: | Yaari, Gur, Uduman, Mohamed, Kleinstein, Steven H. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3458526/ https://www.ncbi.nlm.nih.gov/pubmed/22641856 http://dx.doi.org/10.1093/nar/gks457 |
Ejemplares similares
-
Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations
por: Yaari, Gur, et al.
Publicado: (2013) -
Detecting selection in immunoglobulin sequences
por: Uduman, Mohamed, et al.
Publicado: (2011) -
Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data
por: Yaari, Gur, et al.
Publicado: (2013) -
Sources of PCR-induced distortions in high-throughput sequencing data sets
por: Kebschull, Justus M., et al.
Publicado: (2015) -
Substantial biases in ultra-short read data sets from high-throughput DNA sequencing
por: Dohm, Juliane C., et al.
Publicado: (2008)