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undergraduate thesis
Određivanje bakterijskih gena rezistentnih na antibiotike
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:791668
Žagar, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Žagar, M. (2024). Određivanje bakterijskih gena rezistentnih na antibiotike (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:791668

Žagar, Marko. "Određivanje bakterijskih gena rezistentnih na antibiotike." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:791668

Žagar, Marko. "Određivanje bakterijskih gena rezistentnih na antibiotike." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:791668

Žagar, M. (2024). 'Određivanje bakterijskih gena rezistentnih na antibiotike', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:791668

Žagar M. Određivanje bakterijskih gena rezistentnih na antibiotike [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:791668

M. Žagar, "Određivanje bakterijskih gena rezistentnih na antibiotike", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:791668

Metadata
TitleOdređivanje bakterijskih gena rezistentnih na antibiotike
Title (english)Identification of bacterial antibiotic resistance genes
AuthorMarko Žagar
MentorMirjana Domazet-Lošo (mentor)
Committee memberMirjana Domazet-Lošo (predsjednik povjerenstva)
Committee memberMihael Kovač (član povjerenstva)
Committee memberAndrej Slapničar (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-06-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Rezistencija na antibiotike je aktualan problem u medicini. Problem je ozbiljan zbog horizontalnog prijenosa gena koji brzo širi rezistenciju između bakterija. Jedan od načina na koji se može identificirati i klasificirati rezistencija su tehnologije umjetne inteligencije poput jezičnih modela i strojnog učenja. U ovom radu sam iskoristio skup javno dostupnih sljedova gena koji stvaraju rezistenciju iz CARD baze podataka te sam s pomoću ESM-1b proteinskog jezičnog modela stvorio numeričke reprezentacije tih gena. Zatim sam trenirao dva XGBoost modela strojnog učenja. Jednog sam trenirao da identificira, a drugog da klasificira gene koji stvaraju rezistenciju. Model može s točnosti od 97 % identificirati uzrokuje li neki gen rezistenciju, a ako gen stvara rezistenciju model može s točnosti od 97 % odrediti na koji je antibiotik gen rezistentan. Takav model bi mogao naći mjesto u praksi kao pomoć prilikom odabira tretmana.
Abstract (english)
Antibiotic resistance is a current problem in medicine. One of the ways to identify and classify resistance is through artificial intelligence technologies such as language models and machine learning. In this study, I utilized a publicly available dataset of resistance gene sequences from the CARD database and used a protein language model to create numerical representations of these genes. I trained two XGBoost machine learning models. One model was trained to identify, and the other to classify genes that confer resistance. The trained model can identify with 97 % accuracy whether a gene causes resistance, and if the gene causes resistance, the model can determine with 97 % accuracy to which antibiotic the gene is resistant. Such a model could find a place in practice as an aid in selecting treatment.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:791668
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 on2024-10-12 22:34:31