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master's thesis
Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera
2023. urn:nbn:hr:190:387312
Ronta, Antonio
University of Rijeka
Faculty of Engineering

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Ronta, A. (2023). Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:387312

Ronta, Antonio. "Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera." Master's thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:387312

Ronta, Antonio. "Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera." Master's thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:387312

Ronta, A. (2023). 'Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 23 April 2025, https://urn.nsk.hr/urn:nbn:hr:190:387312

Ronta A. Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2023 [cited 2025 April 23] Available at: https://urn.nsk.hr/urn:nbn:hr:190:387312

A. Ronta, "Stvaranje novih peptida upotrebom modela varijacijskog autoenkodera", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:190:387312

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Metadata
TitleStvaranje novih peptida upotrebom modela varijacijskog autoenkodera
Title (english)Generating de novo peptides using variational autoencoder model
AuthorAntonio Ronta
MentorGoran Mauša (mentor)
Committee memberIvo Ipšić (predsjednik povjerenstva)
Committee memberSandi Ljubić (član povjerenstva)
Committee memberGoran Mauša (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
Rijeka
Defense date and country2023-11-21, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Rastuća prijetnja rezistencije na antibiotike ističe potrebu za inovativnim terapijskim strategijama. Antimikrobni peptidi (AMP-ovi) su se pojavili kao potencijalni kandidati s izvanrednim antimikrobnim svojstvima. Duboki generativni modeli, posebice varijacijski autoenkoderi (VAE), obećavaju učinkovito generiranje ovih peptida. Ovo istraživanje ispituje primjenu VAE modela za generiranje AMP-ova, ističući njihov potencijal u borbi protiv rezistencije na antibiotike. Naglašava sposobnost VAE... More modela za olakšavanje dizajna AMP-ova, uzimajući u obzir važnost daljnjeg usavršavanja modela kako bi se potpuno iskoristile njihove mogućnosti i optimizirali rezultati. Less
Abstract (english)
The increasing menace of antibiotic resistance underscores the need for innovative therapeutic strategies. Antimicrobial peptides (AMPs) have emerged as potential candidates, exhibiting remarkable antimicrobial properties. Deep generative models, particularly Variational Autoencoders (VAEs), offer promise in the efficient design of these peptides. This study delves into the application of VAEs for AMP generation, highlighting their potential in combating antibiotic resistance. It... More underscores VAEs’ ability to facilitate AMP design while recognizing the importance of further model refinement to fully unleash their capabilities and optimize outcomes. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:387312
Study programmeTitle: Computer Engineering
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
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-11-16 18:35:21
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