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Mass spectrometry (MS) -based proteomics has evolved into an important tool applied in biological as well as medical research. In his PhD thesis, MSc Tommi Välikangas comprehensively evaluated computational tools for different steps of MS data processing.

Often the data produced by the mass spectrometer includes a considerable amount of technical noise and incomplete measurements, which can bias the true underlying biological signal and make it more difficult to be detected correctly. The data from the MS instrument needs to be “normalized” to remove such biasing technical variation and make the samples comparable with each other.

-In my thesis, I evaluated computational tools for different steps of processing label-free MS data ranging from the normalization of the data to choosing a suitable preprocessing software and dealing with missing values. The thesis aims to find best practices where applicable. The proper use of such computational tools eventually enables the efficient analysis of MS data and its refinement into biological or medical understanding, Välikangas says.

A new computational tool for detecting differences in protein expression between two conditions in longitudinal studies, especially tolerant for technical noise and missing measurement values, was developed as a part of the dissertation. The developed tool enables the robust and accurate detection of the true biological signal from MS data.  In addition, the further refinement of the discovered protein findings into practical biological knowledge through integrated enrichment and network analysis, is investigated in the thesis. The effective visualization of such functional networks enables fast interpretation of the most important results and the selection of the most interesting findings for future studies.

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MSc Tommi Välikangas presents his thesis “Enhanced label-free discovery proteomics through improved data analysis and knowledge enrichment” for public examination in the University of Turku on Friday February 11th at 12:00 (Vierailukeskus Joki, Putous-auditorio, Lemminkäisenkatu 12 b, Turku). Audience can also follow the defence remotely: https://utu.zoom.us/j/69021419015

Research director Markku Varjosalo (University of Helsinki) has been nominated as the opponent, and Professor Laura Elo (University of Turku) as the custos. The field of study is computer sciences and the language of the dissertation will be English.

The thesis has been published online: https://urn.fi/URN:ISBN:978-951-29-8742-9

The University of Turku actively follows the coronavirus situation and the authorities’ instructions. The University may change the instructions according to the situation.

Audience arriving to a dissertation defence organised at the University’s facilities are mainly required to present a COVID-19 certificate. The certificate is required from everyone over 16 who are not the University’s personnel or students.