Iterativna optimizacija modela i pretraživanje proteoma

master's thesis

• Author: Maja Cigula
• Mentor: Pavle Goldstein (mentor)
• Committee member: Pavle Goldstein (predsjednik povjerenstva)
• Committee member: Zvonimir Tutek (član povjerenstva)
• Committee member: Franka Miriam Bruckler (član povjerenstva)
• Committee member: Maja Starčević (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2016-02-24, 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: distribucije ekstremnih vrijednosti; string matching metoda; sliding window metoda
• Keywords (english): extreme value distribution; string matching algorithm; sliding window algorithm
• Language: croatian
• URN:NBN: urn:nbn:hr:217:877304
• Study programme: Title: Mathematical Statistics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2019-01-07 10:15:53