Article ; Online: Using interpretable machine learning to extend heterogeneous antibody-virus datasets.
Cell reports methods
2023 Volume 3, Issue 8, Page(s) 100540
Abstract: A central challenge in biology is to use existing measurements to predict the outcomes of future experiments. For the rapidly evolving influenza virus, variants examined in one study will often have little to no overlap with other studies, making it ... ...
Abstract | A central challenge in biology is to use existing measurements to predict the outcomes of future experiments. For the rapidly evolving influenza virus, variants examined in one study will often have little to no overlap with other studies, making it difficult to discern patterns or unify datasets. We develop a computational framework that predicts how an antibody or serum would inhibit any variant from |
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MeSH term(s) | Animals ; Humans ; Ferrets ; Antibodies ; Hemagglutination Inhibition Tests ; Machine Learning ; Oils, Volatile |
Chemical Substances | Antibodies ; Oils, Volatile |
Language | English |
Publishing date | 2023-07-25 |
Publishing country | United States |
Document type | Journal Article ; Research Support, Non-U.S. Gov't |
ISSN | 2667-2375 |
ISSN (online) | 2667-2375 |
DOI | 10.1016/j.crmeth.2023.100540 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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