Matching peptide sequences with mass spectra

K. W. Lau, B. Stapley, S. Hubbard, H. Yin

    Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

    Abstract

    We study a method of mapping both mass spectra and sequences to feature vectors and the correlation between them. The method of calculating the feature vector from mass spectra is presented, together with a method for representing sequences. A correlation metric comparing both representations is studied. It shows strong correlation between two representation for the same peptides. It also demostrates that the effect of correlation is increased by using the longer sequences induced from the theoretical mass spectra. The method provides a promising step towards de novo sequencing. © Springer-Verlag Berlin Heidelberg 2005.
    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science|Lect. Notes Comput. Sci.
    EditorsM. Gallagher, J. Hogan, F. Maire
    PublisherSpringer Nature
    Pages390-397
    Number of pages7
    Volume3578
    Publication statusPublished - 2005
    Event6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005 - Brisbane
    Duration: 1 Jul 2005 → …

    Conference

    Conference6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005
    CityBrisbane
    Period1/07/05 → …

    Fingerprint

    Dive into the research topics of 'Matching peptide sequences with mass spectra'. Together they form a unique fingerprint.

    Cite this