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undergraduate thesis
Model predviđanja antimikrobnih peptida
2020. urn:nbn:hr:190:527432
Erjavac, Ivan
University of Rijeka
Faculty of Engineering
Department of Computer Engineering
Section of Intelligent Computing Systems

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Erjavac, I. (2020). Model predviđanja antimikrobnih peptida (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:527432

Erjavac, Ivan. "Model predviđanja antimikrobnih peptida." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:190:527432

Erjavac, Ivan. "Model predviđanja antimikrobnih peptida." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2020. https://urn.nsk.hr/urn:nbn:hr:190:527432

Erjavac, I. (2020). 'Model predviđanja antimikrobnih peptida', Undergraduate thesis, University of Rijeka, Faculty of Engineering, accessed 09 July 2024, https://urn.nsk.hr/urn:nbn:hr:190:527432

Erjavac I. Model predviđanja antimikrobnih peptida [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2020 [cited 2024 July 09] Available at: https://urn.nsk.hr/urn:nbn:hr:190:527432

I. Erjavac, "Model predviđanja antimikrobnih peptida", Undergraduate thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:190:527432

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Metadata
TitleModel predviđanja antimikrobnih peptida
Title (english)Prediction of antimicrobial peptides
AuthorIvan Erjavac
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 Intelligent Computing Systems)
Rijeka
Defense date and country2020-09-16, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom je radu predstavljeno svo znanje potrebno za razumijevanje teme strojnog učenja, te kako je strojno učenje primjenjivo u svrhe predviđanja antimikrobnih peptida. Također, opisan je postupak konstruiranja dosad nepostojećeg seta podataka putem istraživanja teme antimikrobnih peptida, pronalaska izvora podataka i značajki koje opisuju te podatke. Korištenjem standarnih alata, programskih jezika i knjižnica koje se upotrebljavaju na području strojnog učenja, stvoren je model koji sa točnošću od 91.5% predviđa ima li zadani peptid antimikrobnu aktivnost ili nema.
Abstract (english)
This paper defines all the knowledge needed to understand the topic of machine learning, and how machine can be leveraged for the purpose of predicting antimicrobial peptides. This paper also describes the construction of a dataset from scratch, through research of the topic of antimicrobial peptides, finding data sources, and discovering the features that describe the data. Using standardized tools, programming languages and machine learning libraries, a model was developed that predicts antimicrobial activity in peptides with an accuracy of 91.5%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:527432
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 conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2021-09-30 07:45:46