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master's thesis
Klasifikacija DNA sljedova korištenjem modela dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:061841
Matečić, Jelena
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Matečić, J. (2024). Klasifikacija DNA sljedova korištenjem modela dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:061841

Matečić, Jelena. "Klasifikacija DNA sljedova korištenjem modela dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:061841

Matečić, Jelena. "Klasifikacija DNA sljedova korištenjem modela dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:061841

Matečić, J. (2024). 'Klasifikacija DNA sljedova korištenjem modela dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:061841

Matečić J. Klasifikacija DNA sljedova korištenjem modela dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:061841

J. Matečić, "Klasifikacija DNA sljedova korištenjem modela dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:061841

Metadata
TitleKlasifikacija DNA sljedova korištenjem modela dubokog učenja
Title (english)Deep-learning based DNA sequence classification
AuthorJelena Matečić
MentorMirjana Domazet-Lošo (mentor)
Committee memberMirjana Domazet-Lošo (predsjednik povjerenstva)
Committee memberBoris Milašinović (član povjerenstva)
Committee memberDanijel Mlinarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-04, Croatia
Abstract
U radu se objašnjava arhitektura transformera i motivacija za njezino korištenje u rješavanju problema klasifikacije DNA sljedova. Opisana je ostvarena arhitektura korištenjem programskog jezika Python. Opisane su dvije metode pripreme skupa podataka za treniranje modela: k-mer i label encoding. Uspoređeni su rezultati varijacija hiperparametara modela i korištenja različitih tehnika ugrađivanja ulaza. Rezultati najboljeg modela uspoređeni su s rezultatima iz referentnog rada. Arhitektura transformera u kombinaciji s podacima nad kojima se koristila k-mer tehnika ugrađivanja ulaza pokazala se jako uspješnom.
Abstract (english)
This master thesis focuses on the transformer architecture and the motivation for its use in solving the problem of DNA sequence classification. The architecture was implemented using the Python programming language. The two methods used for the data set preparation are described: the k-mer and the label encoding. The results of variations of model hyperparameters and the use of different input embedding techniques were compared. The best model's results were compared with those from the reference work. When combined with data embedded using the k-mer embedding technique, the transformer architecture has proven to be highly effective.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:061841
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 21:30:34