Statistical Analysis of PAR-CLIP data
Independent thesis Advanced level (degree of Master (Two Years)), 60 credits / 90 HE creditsStudent thesis
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 preprocessing 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.
Place, publisher, year, edition, pages
2013. , 50 p.
statistical modeling, PAR-CLIP, RNA-binding proteins, Bayesian analysis
Bioinformatics (Computational Biology)
IdentifiersURN: urn:nbn:se:kth:diva-124347OAI: oai:DiVA.org:kth-124347DiVA: diva2:634135
Master of Science - Systems Biology
Aurell, Erik, ProfessorLähdesmäki, Harri, ProfessorBeerenwinkel, Niko, Professor
Aurell, Erik, Professor