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undergraduate thesis
Računalni model za procjenu sklonosti agregaciji peptida i proteina
Rijeka: University of Rijeka, Faculty of Engineering, 2021. urn:nbn:hr:190:145697
Žužić, Lucija
University of Rijeka
Faculty of Engineering
Department of Computer Engineering
Section of Software Engineering

Institutional repository: Repository of the University of Rijeka, Faculty of Engineering

Cite this document

Žužić, L. (2021). Računalni model za procjenu sklonosti agregaciji peptida i proteina (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:145697

Žužić, Lucija. "Računalni model za procjenu sklonosti agregaciji peptida i proteina." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2021. https://urn.nsk.hr/urn:nbn:hr:190:145697

Žužić, Lucija. "Računalni model za procjenu sklonosti agregaciji peptida i proteina." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2021. https://urn.nsk.hr/urn:nbn:hr:190:145697

Žužić, L. (2021). 'Računalni model za procjenu sklonosti agregaciji peptida i proteina', Undergraduate thesis, University of Rijeka, Faculty of Engineering, accessed 24 December 2024, https://urn.nsk.hr/urn:nbn:hr:190:145697

Žužić L. Računalni model za procjenu sklonosti agregaciji peptida i proteina [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2021 [cited 2024 December 24] Available at: https://urn.nsk.hr/urn:nbn:hr:190:145697

L. Žužić, "Računalni model za procjenu sklonosti agregaciji peptida i proteina", Undergraduate thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:190:145697

Metadata
TitleRačunalni model za procjenu sklonosti agregaciji peptida i proteina
Title (english)Aggregation propensity estimation model for peptides and proteins
AuthorLucija Žužić
MentorGoran Mauša (mentor)
Committee memberKristijan Lenac (predsjednik povjerenstva)
Committee memberGoran Mauša (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Computer Engineering)
(Section of Software Engineering)
Rijeka
Defense date and country2021-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Motivirani metodom za računalnu analizu sklonosti agregaciji proteina zasnovanoj na tehnici kliznog prozora, izrađeni su modeli koji svoj izračun temelje na poznatim sklonostima agregaciji aminokiselina, dipeptida i tripeptida. Uspješnost stvorenih metoda procijenjena je usporedbom regija sklonih agregaciji koje je otkrila svaka od njih. Analizirani su koeficijenti korelacije za rezultate novih metoda te za odabrana fizikalna i kemijska svojstva peptida kako bi se otkrilo koji su od njih pouzdani indikatori samosastavljanja. Uzevši u obzir svojstva za koje AUC iznosi više od 0,5 izgrađen je i model predviđanja sklonosti prema samosastavljanju te je primijenjen za skup dizajniranih peptida. Postotak nepolarnih aminokiselina u peptidu pokazao se kao najuspješnije svojstvo te je za metriku vrednovanja AUC postiglo 0,802.
Abstract (english)
Motivated by a method for computer-based analysis of the aggregation propensity of proteins built on a sliding window tehnique, new models, that base their calculations on known aggregation propensities of aminoacids, dipeptides or tripeptides, were made. The successfulness of the created methods was evaluated by comparing the aggregation-prone regions that each of them discovered. Correlation coefficients were analysed for the results of the new methods and for the selected physical and chemical properties of peptides in order to discover which of them are reliable indicators of self-assembly. Taking into consideration properties for which AUC was more than 0,5, a model for the prediction of self-assembly was built and applied to a set of designed peptides. NonPolar Mole% displayed itself as the most successful property and it achieved a value of 0,802 for the AUC evaluation metric.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:145697
Study programmeTitle: Computer Engineering
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
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2021-10-11 10:28:39