Thesis icon

Thesis

Protein language representation learning to predict SARS-CoV-2 mutational landscape

Abstract:

With the proliferation of SARS-CoV-2 pandemic globally, numerous variants have been emerging on a daily basis containing distinct transmission and infection rates, risks and impact over evasion of antibody neutralisation. Early discovery of high-risk mutations is critical towards undertaking data-informed therapeutic design decisions and effective pandemic management. This dissertation explores the application of Language Models, commonly used for textual processing, to decipher SARS-CoV-2...

Expand abstract

Actions


Access Document


Files:

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Oxford college:
St Anne's College
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Role:
Supervisor
ORCID:
0000-0002-1779-6741
Type of award:
MSc
Level of award:
Masters
Awarding institution:
University of Oxford
DOI:

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP