Ab Initio prediction of molecular fragments from tandem mass spectrometry data

Markus Heinonen, Ari Rantanen, Taneli Mielikäinen, Esa Pitkänen, Juha T. Kokkonen, Juho Rousu

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Mass spectrometry is one of the key enabling measurement technologies for
systems biology, due to its ability to quantify molecules in small concentrations. Tandem mass spectrometers tackle the main shortcoming of mass spectrometry, the fact that molecules with an equal mass-to-charge ratio are not separated. In tandem mass spectrometer molecules can be fragmented and the intensities of these fragments measured as well. However, this creates a need for methods for identifying the generated fragments.

In this paper, we introduce a novel combinatorial approach for predicting the structure of molecular fragments that first enumerates all possible fragment candidates and then ranks them according the cost of cleaving a fragment from a molecule. Unlike many existing methods, our method does not rely on hand-coded fragmentation rule databases. Our method is able to predict the correct fragmentation of small-to-medium sized molecules with high accuracy.
Original languageEnglish
Title of host publicationProceedings of the German Conference on Bioinformatics
EditorsDaniel Huson, Oliver Kohlbacher, Andrei Lupas, Kay Nieselt, Andreas Zell
PublisherGesellschaft für Informatik (GI)
ISBN (Print)978-3-88579-177-5
Publication statusPublished - 2006
MoE publication typeA4 Article in a conference publication
EventGerman Conference on Bioinformatics - Tübingen, Germany
Duration: 19 Sep 200622 Sep 2006

Publication series

NameLecture Notes in Informatics (LNI)
PublisherGesellschaft für Informatik


ConferenceGerman Conference on Bioinformatics
Abbreviated titleGCB

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