Predicting and Analyzing HIV-1 Adaptation to Broadly Neutralizing Antibodies 
and the Host Immune System Using Machine Learning

Hake, Anna

doi:10.22028/D291-39532

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Thesis

Predicting and Analyzing HIV-1 Adaptation to Broadly Neutralizing Antibodies and the Host Immune System Using Machine Learning

MPS-Authors

/persons/resource/persons79256

Hake, Anna
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

External Resource

https://scidok.sulb.uni-saarland.de/handle/20.500.11880/35743
(Any fulltext)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Hake, A. (2023). Predicting and Analyzing HIV-1 Adaptation to Broadly Neutralizing Antibodies and the Host Immune System Using Machine Learning. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-39532.

Cite as: https://hdl.handle.net/21.11116/0000-000D-10E8-B

Abstract

There is no abstract available