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International Conference on Research in Computational Molecular Biology

RECOMB 2011: Research in Computational Molecular Biology pp 298–319Cite as

Blocked Pattern Matching Problem and Its Applications in Proteomics

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6577))

Abstract

Matching a mass spectrum against a text (a key computational task in proteomics) is slow since the existing text indexing algorithms (with search time independent of the text size) are not applicable in the domain of mass spectrometry. As a result, many important applications (e.g., searches for mutated peptides) are prohibitively time-consuming and even the standard search for non-mutated peptides is becoming too slow with recent advances in high-throughput genomics and proteomics technologies. We introduce a new paradigm – the Blocked Pattern Matching (BPM) Problem - that models peptide identification. BPM corresponds to matching a pattern against a text (over the alphabet of integers) under the assumption that each symbol a in the pattern can match a block of consecutive symbols in the text with total sum a.

BPM opens a new, still unexplored, direction in combinatorial pattern matching and leads to the Mutated BPM (modeling identification of mutated peptides) and Fused BPM (modeling identification of fused peptides in tumor genomes). We illustrate how BPM algorithms solve problems that are beyond the reach of existing proteomics tools.

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Author information

Authors and Affiliations

  1. Bioinformatics and Systems Biology Program, University of California, San Diego, USA

    Julio Ng

  2. Department of Computer Science, Bar-Ilan University, Israel

    Amihood Amir

  3. Department of Computer Science, Johns Hopkins University, USA

    Amihood Amir

  4. Department of Computer Science and Eng., University of California, San Diego, USA

    Pavel A. Pevzner

Authors
  1. Julio Ng
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  2. Amihood Amir
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  3. Pavel A. Pevzner
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Editor information

Editors and Affiliations

  1. EBU3b, University of California San Diego, #4218, 9500 Gilman Drive, 92093-0404, La Jolla, CA, USA

    Vineet Bafna

  2. School of Computing Science, Simon Fraser University, 8888 University Drive, V5A 1S6, Burnaby, BC, Canada

    S. Cenk Sahinalp

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Ng, J., Amir, A., Pevzner, P.A. (2011). Blocked Pattern Matching Problem and Its Applications in Proteomics. In: Bafna, V., Sahinalp, S.C. (eds) Research in Computational Molecular Biology. RECOMB 2011. Lecture Notes in Computer Science(), vol 6577. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20036-6_27

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  • DOI: https://doi.org/10.1007/978-3-642-20036-6_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20035-9

  • Online ISBN: 978-3-642-20036-6

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