Tesi etd-02192020-165904 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
BACHINI, FRANCESCO
URN
etd-02192020-165904
Titolo
On the use of sequential learning models to estimate natural selection on HIV from clinical samples
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Bacciu, Davide
Parole chiave
- gru
- hiv
- machine learning
- selection coefficient
Data inizio appello
06/03/2020
Consultabilità
Tesi non consultabile
Riassunto
The thesis deals with the analysis of artificial and real-world clinical data concerning natural selection on the HIV virus. A sampling algorithm has been implemented to generate synthetic data for preliminary validation and training set expansion. A recurrent neural architecture has been deployed, trained and tested on the task of estimating the selection coefficient in the HIV virus.
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