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Automatic detection of protein degradation markers in mass spectrometry imaging
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
2016 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Today we are collecting a large amount of tissue samples to store for future studies of different health conditions, in hopes that the focus in health care will shift from treatments to early detection and prevention, by the use of biomarkers. To make sure that the storing of tissue is done in a reliable way, where the molecular profile of the samples are preserved, we first need to characterise how these changes occur. In this thesis, data from mice brains were collected using MALDI imaging mass spectrometry (IMS) and an analysis pipeline for robust MALDI IMS data handling and evaluation was implemented. The finished pipeline contains two reduction algorithms, catching images with interesting intensity features, while taking the spatial information into account, along with a robust similarity measurement, for measuring the degree of co-localisation. It also includes a clustering algorithm built upon the similarity measurement and an amino acid mass comparer, iteratively generating combinations of amino acids for further mass comparisons with mass differences between cluster members.

Availability: The source code is available at https://github.com/stephanieherman/thesis

Place, publisher, year, edition, pages
2016. , 56 p.
Series
UPTEC X, 15038
Keyword [en]
Imaging Mass Spectrometry, Matrix-Assisted Laser Desorption-Ionization, Image Analysis, Protein Degradation, Heat Stabilization, Brain, Mice
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-275072OAI: oai:DiVA.org:uu-275072DiVA: diva2:898727
Educational program
Molecular Biotechnology Engineering Programme
Supervisors
Examiners
Available from: 2016-01-29 Created: 2016-01-28 Last updated: 2016-01-29Bibliographically approved

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Bioinformatics (Computational Biology)

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
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