English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models

Hake, A., Germann, A., de Beer, C., Thielen, A., Däumer, M., Preiser, W., et al. (2023). Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models. PLOS Computational Biology, 19(12): e1010355. doi:10.1371/journal.pcbi.1010355.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-000E-5B0F-D Version Permalink: https://hdl.handle.net/21.11116/0000-000E-5B12-8
Genre: Journal Article
Latex : Insights to {HIV}-1 coreceptor usage by estimating {HLA} adaptation with {B}ayesian generalized linear mixed models

Files

show Files
hide Files
:
pcbi.1010355.pdf (Publisher version), 2MB
View   Save
File Permalink:
https://hdl.handle.net/21.11116/0000-000E-5B11-9
Name:
pcbi.1010355.pdf
Description:
-
OA-Status:
Gold
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
View
Copyright Date:
-
Copyright Info:
Copyright: ©2023 Hake et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
License:
-

Locators

show

Creators

show
hide
 Creators:
Hake, Anna1, Author           
Germann, Anja2, Author
de Beer, Corena2, Author
Thielen, Alexander2, Author           
Däumer, Martin2, Author
Preiser, Wolfgang2, Author
von Briesen, Hagen2, Author
Pfeifer, Nico2, Author           
Affiliations:
1Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society, ou_40046              
2External Organizations, ou_persistent22              

Content

show

Details

show
hide
Language(s): eng - English
 Dates: 20232023
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: hake23
DOI: 10.1371/journal.pcbi.1010355
PMC: PMC10769057
PMID: 38127856
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: PLOS Computational Biology
  Abbreviation : PLOS Comput Biol
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: San Francisco, CA : Public Library of Science
Pages: 21 p. Volume / Issue: 19 (12) Sequence Number: e1010355 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1