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undergraduate thesis
Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:615104
Grgurević, Ante
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Grgurević, A. (2021). Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:615104

Grgurević, Ante. "Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:615104

Grgurević, Ante. "Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:615104

Grgurević, A. (2021). 'Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 05 October 2024, https://urn.nsk.hr/urn:nbn:hr:168:615104

Grgurević A. Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 October 05] Available at: https://urn.nsk.hr/urn:nbn:hr:168:615104

A. Grgurević, "Simulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:615104

Metadata
TitleSimulacija de-novo sekvenciranja kratkih proteina pomoću masenog spektrometra, koristeći vjerojatnosne modele
Title (english)Simulating Short Protein De-novo Sequencing by Mass Spectrometry Using Probabilistic Models
AuthorAnte Grgurević
MentorKrešimir Križanović (mentor)
Committee memberKrešimir Križanović (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberFilip Bosnić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
De-novo sekvenciranje kratkih proteina je proces u kojem dobivamo sekvencu aminokiselina iz podataka iščitanih iz masenog spektrometra. Prednost de-novo sekvenciranja je sposobnost dobivanja sekvence bez prethodne identifikacije peptida u bazi podataka. Čest problem kod pristupa koji koristi bazu podataka se temelji na činjenici da peptidi mogu biti derivirani iz nepoznatih proteina, ili pak mogu proći kroz brojne posttranslacijske ili kemijske modifikacije. Za potrebe de-novo sekvenciranje, treba nam izlaz iz masenog spektrometra koji je generiran pomoću simulatora razvijenog u suradnji sa kolegom Andrijom Arbanasićem. Koristeći modificirani algoritam za rješavanje problema ruksaka, pronalazimo sekvencu aminokiselina koja odgovara rješenju problema. Nedvojbeno suboptimalni rezultati i preciznost programa su posljedica kompleksnosti problema te mnogih komplikacija kod samog određivanja sekvence aminokiselina koje su navedene u samom radu.
Abstract (english)
Short protein de-novo sequencing is a process in which we get an aminoacid sequence from the data read from mass spectrometer. One of the advantages of de-novo sequencing is the ability to provide an aminoacid sequence without previous peptide identification in the database. One of the most reccurring problems in approaches that use database identification is that peptides can be derived from unknown proteins, or they can go through many post-translational or chemical modifications. For short protein de-novo sequencing, we need outputs gained from mass spectrometer, which are generated with the help of mass spectrometry simulator that has been developed in colaboration with Andrija Arbanasić. Using the modified knapsack problem algorithm, we find an aminoacid sequence that represents the solution to the problem. Undoubtedly suboptimal results and software accuracy are consequences of problem complexity and many more complications brought to light when trying to predict amino-acid sequence, which have been covered in this study.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:615104
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)
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File originBorn digital
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Created on2023-01-15 10:14:28