search query: @keyword bayesian analysis / total: 4
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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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