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undergraduate thesis
Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:099323
Unković, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Unković, I. (2023). Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:099323

Unković, Ivan. "Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:099323

Unković, Ivan. "Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:099323

Unković, I. (2023). 'Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 10 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:099323

Unković I. Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 July 10] Available at: https://urn.nsk.hr/urn:nbn:hr:168:099323

I. Unković, "Ablacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:099323

Metadata
TitleAblacija dubokih neuronskih mreža za predviđanje epigenetskih modifikacija
Title (english)Ablation study of deep neural networks for predicting epigenetic modifications
AuthorIvan Unković
MentorMile Šikić (mentor)
Committee memberMile Šikić (predsjednik povjerenstva)
Committee memberRafael Josip Penić (član povjerenstva)
Committee memberFilip Tomas (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Glavni cilj bioinformatike je pronalazak novih odgovora u području analize genoma, koje ima važnu ulogu u očuvanju i poboljšanju kvalitete života. Neka pitanja na koja se traži odgovor tiču se DNA-metilacije, koja je svojevrsna modifikacija DNA niti. Danas se istraživanja vezanu uz tu modifikaciju sve više provode korištenjem algoritama strojnog učenja. Rockfish je jedan takav model koji se temelji na transformatoru koji koristi neuronske mreže za pronalaženje metiliranih elemenata u DNA niti. U ovom radu, korištenjem programskog jezika Python, neki dijelovi modela su uklonjeni, i time se provodi ablacija, a ponekad i dodatno trenirani kako bi se primijetio utjecaj različitih komponenti i utvrdile njihove važnosti. Rezultati ablacije proučavaju se kroz četiri različite usporedbe, gdje se procjenjuju točnost, preciznost, odziv i specifičnost svakog modela. Modeli se zatim uspoređuju, a komponente modela rangiraju se prema njihovim rezultatima. Zaključci se donose na temelju dobivenih rezultata.
Abstract (english)
The main goal of bioinformatics is to find new answers regarding genome analysis and the field is an important factor in preserving and improving the quality of life. Some questions that need to be answered are regarding DNA methylation, which is a modification of the DNA strand. Nowadays, research is increasingly conducted by utilizing machine learning algorithms. Rockfish is a transformer based-model that uses neural networks to find which elements of the DNA strand are methylated. In this thesis, by using Python programming language, some components of the model are removed, thus performing ablation, and sometimes trained additionally so that the impact of the given components and their importance could be noticed. The results of the ablation study are inspected through four different comparisons, where the accuracy, precision, recall, and specificity of each model are evaluated. The models are then compared and the components of the model are ranked based on their results. Conclusions are made based on the results that were obtained.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:099323
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-10-11 10:51:22