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Identification and visualization of splice variants in shotgun proteomics data by Alternative Splicing Database
KTH, School of Biotechnology (BIO).
2013 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

It has been shown in many studies that alternative splicing plays an important role in functional regulation and is associated with many neurological disorders and cancers. Current methods to detect splice variants are computational prediction by ESTs clustering and experimental approaches such as RNA probe microarray. These methods are only focusing on the the RNA level. But due to post transcriptional modification on pre-mRNA molecules, there is a weak correlation between mRNA abundance and protein expressin. Therefore, it is important to find evidence of these functioinally important splice variants at the protein level. Shotgun proteomics has become a favorable tool to do large scale identification of proteins. Recently, a tool called Protein Quantification and Peptide Quality Control (PQPQ) was develope to enhance information output from shotgun proteomics data and to detect protein variants. Here, we present a downstream program, SpliceView, a tool for analyzing and visualizing the output from PQPQ for finding splice variants. Proteomics data of A431 cell line was used to exemplify available functions of SpliceView.

Place, publisher, year, edition, pages
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Engineering and Technology
URN: urn:nbn:se:kth:diva-173925OAI: diva2:856188
Available from: 2015-09-24 Created: 2015-09-23 Last updated: 2015-09-24Bibliographically approved

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