prikaz prve stranice dokumenta Identifikacija RNA izoformi iz grafa transkripata
No public access
master's thesis
Identifikacija RNA izoformi iz grafa transkripata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2015. urn:nbn:hr:168:950171
Pavlović, Dario
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Pavlović, D. (2015). Identifikacija RNA izoformi iz grafa transkripata (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:950171

Pavlović, Dario. "Identifikacija RNA izoformi iz grafa transkripata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2015. https://urn.nsk.hr/urn:nbn:hr:168:950171

Pavlović, Dario. "Identifikacija RNA izoformi iz grafa transkripata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2015. https://urn.nsk.hr/urn:nbn:hr:168:950171

Pavlović, D. (2015). 'Identifikacija RNA izoformi iz grafa transkripata', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 24 April 2024, https://urn.nsk.hr/urn:nbn:hr:168:950171

Pavlović D. Identifikacija RNA izoformi iz grafa transkripata [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2015 [cited 2024 April 24] Available at: https://urn.nsk.hr/urn:nbn:hr:168:950171

D. Pavlović, "Identifikacija RNA izoformi iz grafa transkripata", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2015. Available at: https://urn.nsk.hr/urn:nbn:hr:168:950171

Please login to the repository to save this object to your list.
Metadata
TitleIdentifikacija RNA izoformi iz grafa transkripata
Title (english)Splice Isoform Identification from Transcript Graphs
AuthorDario Pavlović
MentorMile Šikić (mentor)
Committee memberMile Šikić (predsjednik povjerenstva)
Committee memberDamir Seršić (član povjerenstva)
Committee memberMladen Vučić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2015-07-03, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Mjerenje relativnih količina RNA transkripata u uzorku može biti vrlo važno za različite primjene u biologiji i medicini. Sekvenciranje sljedeće generacije postaje primarno korištena tehnologija za omogućavanje takvih analiza pružanjem osnovnih podataka o uzorku. U ovome radu, prezentirao sam statistički model procjene količine RNA koji koristi očitanja sekvenciranja sljedeće generacije s ciljem pronalaženja optimalnih vrijednosti relativnih količina. isomorph, programska implementacija ovog modela je opisana u radu. isomorph pokušava pronaći maksimum funkcije izglednosti po parametrima koji predstavljaju relativne nivoe prisutnosti transkripata u uzorku. Testiranje je pokazalo da za očitanja bez parova, isomorph ima zadovoljavajuću točnost, dok za očitanja u parovima pokazuje potrebu za dodatnim poboljšanjima performansi. Dostupan je na https://github.com/darxsys/isomorph.
Abstract (english)
Providing a measure of abundances of different RNA transcripts in a sample can be very important in many different biological or medical studies. Next-generation sequencing is becoming a technology of choice for providing fundamental data for such analyses. In this work, I have presented an RNA abundance estimation model that uses next-generation RNA-Seq reads to estimate optimal relative transcript abun- dance values. isomorph, a software implementation of this method is presented and explained. isomorph tries to maximize a likelihood function with regards to isoform abundance levels to provide an optimal estimate of relative transcript abun- dances in a sample. Testing has shown that for single-end reads, isomorph performs well, while paired-end data performance should be more improved. It is available at https://github.com/darxsys/isomorph.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:950171
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
RepositoryFER Repository
Created on2018-02-06 11:07:03

(©) Nacionalna i sveučilišna knjižnica u Zagrebu 2015. Sva prava pridržana. | Hrvatske bratske zajednice 4 p.p. 550, 10000 Zagreb, Hrvatska Tel. ++ 385 1 616-4040
OIB: 84838770814 | IBAN: HR66 2340 0091 1000 1008 1, Porezni broj (PDV identifikacijski broj) - VAT Number: HR84838770814
Prijava u repozitorij