ETD system

Electronic theses and dissertations repository

 

Tesi etd-02192020-165904


Thesis type
Tesi di laurea magistrale
Author
BACHINI, FRANCESCO
URN
etd-02192020-165904
Title
On the use of sequential learning models to estimate natural selection on HIV from clinical samples
Struttura
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Supervisors
relatore Bacciu, Davide
Parole chiave
  • gru
  • hiv
  • machine learning
  • selection coefficient
Data inizio appello
06/03/2020;
Consultabilità
Secretata d'ufficio
Riassunto analitico
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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