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master's thesis
Iterativna optimizacija modela i pretraživanje proteoma
Zagreb: University of Zagreb, Faculty of Science, 2016. urn:nbn:hr:217:877304
Cigula, Maja
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Cigula, M. (2016). Iterativna optimizacija modela i pretraživanje proteoma (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:877304

Cigula, Maja. "Iterativna optimizacija modela i pretraživanje proteoma." Master's thesis, University of Zagreb, Faculty of Science, 2016. https://urn.nsk.hr/urn:nbn:hr:217:877304

Cigula, Maja. "Iterativna optimizacija modela i pretraživanje proteoma." Master's thesis, University of Zagreb, Faculty of Science, 2016. https://urn.nsk.hr/urn:nbn:hr:217:877304

Cigula, M. (2016). 'Iterativna optimizacija modela i pretraživanje proteoma', Master's thesis, University of Zagreb, Faculty of Science, accessed 23 December 2024, https://urn.nsk.hr/urn:nbn:hr:217:877304

Cigula M. Iterativna optimizacija modela i pretraživanje proteoma [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2016 [cited 2024 December 23] Available at: https://urn.nsk.hr/urn:nbn:hr:217:877304

M. Cigula, "Iterativna optimizacija modela i pretraživanje proteoma", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:217:877304

Metadata
TitleIterativna optimizacija modela i pretraživanje proteoma
AuthorMaja Cigula
MentorPavle Goldstein (mentor)
Committee memberPavle Goldstein (predsjednik povjerenstva)
Committee memberZvonimir Tutek (član povjerenstva)
Committee memberFranka Miriam Bruckler (član povjerenstva)
Committee memberMaja Starčević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2016-02-24, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Nakon kratkog pregleda osnovnih pojmova teorije vjerojatnosti, upoznajemo se sa distribucijama ekstremnih vrijednosti. Opisujemo dvije metode pomoću kojih tražimo karakteristične članove GDSL familije proteina. String matching metoda je uspoređena sa sliding window metodom i opisan je model pomoću kojega određujemo pozitivno rangirane nizove. Objašnjeno je zašto pritom maksimalni scorovi prate logističku distribuciju. Obje metode daju vrlo slične rezultate na četiri biljna proteoma što znači da string matching metoda ima potencijal za korištenje u pretraživanju proteoma zadanim motivom.
Abstract (english)
After a brief introduction to elementary probability theory we introduce certain aspects of the theory of extreme value distribution. We describe and compare two algorithms for searching for strings in large datasets - sliding window and string matching algorithm. Using results from extreme value theory and either of the algorithms, we construct an iterative string searching method. The results of this procedure are compared between the algorithms as well as against expert knowledge, on four plant proteomes.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:877304
Study programmeTitle: Mathematical Statistics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2019-01-07 10:15:53