Building a standard operating procedure for the analysis of mass spectrometry data
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Mass spectrometry (MS) is used in peptidomics to find novel endogenous peptides that may lead to the discovery of new biomarkers. Identifying endogenous peptides from MS is a time-consuming and challenging task; storing identified peptides in a database and comparing them against unknown peptides from other MS runs avoids re-doing identification. MS produce large amounts of data, making interpretation difficult. A platform for helping the identification of endogenous peptides was developed in this project, including a library application for storing peptide data. Machine learning methods were also used to try to find patterns in peptide abundance that could be correlated to a specific sample or treatment type, which can help focus the identification work on peptides of high interest.
Place, publisher, year, edition, pages
2012. , 68 p.
UPTEC X, 12 021
mass spectrometry, machine learning, peptidomics
masspectrometri, maskinlärning, peptidomics
Bioinformatics and Systems Biology
IdentifiersURN: urn:nbn:se:uu:diva-182149OAI: oai:DiVA.org:uu-182149DiVA: diva2:558583
Molecular Biotechnology Engineering Programme
Andersson, Claes, Dr.
Gustafsson, Mats, Prof.