English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The human body is able to generate a diverse set of high affinity antibodies,the soluble form of B cell receptors (BCRs), that bind to and neutralizeinvading pathogens. The natural development of BCRs must be understood in orderto design vaccines for highly mutable pathogens such as influenza and HIV. BCRdiversity is induced by naturally occurring combinatorial "V(D)J"rearrangement, mutation, and selection processes. Most current methods for BCRsequence analysis focus on separately modeling the above processes. Statisticalphylogenetic methods are often used to model the mutational dynamics of BCRsequence data, but these techniques do not consider all the complexitiesassociated with B cell diversification such as the V(D)J rearrangement process.In particular, standard phylogenetic approaches assume the DNA bases of theprogenitor (or "naive") sequence arise independently and according to the samedistribution, ignoring the complexities of V(D)J rearrangement. In this paper,we introduce a novel approach to Bayesian phylogenetic inference for BCRsequences that is based on a phylogenetic hidden Markov model (phylo-HMM). Thistechnique not only integrates a naive rearrangement model with a phylogeneticmodel for BCR sequence evolution but also naturally accounts for uncertainty inall unobserved variables, including the phylogenetic tree, via posteriordistribution sampling.

A Bayesian Phylogenetic Hidden Markov Model for B Cell Receptor Sequence Analysis