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Author:Golumbeanu, Monica
Title:Statistical analysis of PAR-CLIP data
Publication type:Master's thesis
Publication year:2013
Pages:51      Language:   eng
Department/School:Perustieteiden korkeakoulu
Main subject:Informaatiotekniikka   (T-61)
Supervisor:Lähdesmäki, Harri ; Aurell, Erik ; Beerenwinkel, Niko
Instructor:Mohammadi, Pejman
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto     | Archive
Keywords:statistical modeling
PAR-CLIP
RNA-binding proteins
Bayesian analysis
Abstract (eng): From creation to its degradation, the RNA molecule is the action field of many binding proteins with different roles in regulation and RNA metabolism.
Since these proteins are involved in a large number of processes, a variety of diseases are related to abnormalities occurring within the binding mechanisms.
One of the experimental methods for detecting the binding sites of these proteins is PAR-CLIP built on the next generation sequencing technology.
Due to its size and intrinsic noise, PAR-CLIP data analysis requires appropriate pre-processing and thorough statistical analysis.

The present work has two main goals.
First, to develop a modular pipeline for pre-processing PAR-CLIP data and extracting necessary signals for further analysis.
Second, to devise a novel statistical model in order to carry out inference about presence of protein binding sites based on the Signals extracted in the pre-processing step.
ED:2013-09-25
INSSI record number: 47249
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