Improving the identification of antigenic sites in the H1N1 influenza virus through accounting for the experimental structure in a sparse hierarchical Bayesian model. (2019)
Attributed to:
Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.1111/rssc.12338
PubMed Identifier: 31598013
Publication URI: http://europepmc.org/abstract/MED/31598013
Type: Journal Article/Review
Volume: 68
Parent Publication: Journal of the Royal Statistical Society. Series C, Applied statistics
Issue: 4
ISSN: 0035-9254