A Kernel-Based Case Retrieval Algorithm with Application to Bioinformatics

  • Yan Fu
  • Qiang Yang
  • Charles X. Ling
  • Haipeng Wang
  • Dequan Li
  • Ruixiang Sun
  • Hu Zhou
  • Rong Zeng
  • Yiqiang Chen
  • Simin He
  • Wen Gao
Conference paper

DOI: 10.1007/978-3-540-28633-2_58

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3157)
Cite this paper as:
Fu Y. et al. (2004) A Kernel-Based Case Retrieval Algorithm with Application to Bioinformatics. In: Zhang C., W. Guesgen H., Yeap WK. (eds) PRICAI 2004: Trends in Artificial Intelligence. PRICAI 2004. Lecture Notes in Computer Science, vol 3157. Springer, Berlin, Heidelberg

Abstract

Case retrieval in case-based reasoning relies heavily on the design of a good similarity function. This paper provides an approach to utilizing the correlative information among features to compute the similarity of cases for case retrieval. This is achieved by extending the dot product-based linear similarity measures to their nonlinear versions with kernel functions. An application to the peptide retrieval problem in bioinformatics shows the effectiveness of the approach. In this problem, the objective is to retrieve the corresponding peptide to the input tandem mass spectrum from a large database of known peptides. By a kernel function implicitly mapping the tandem mass spectrum to a high dimensional space, the correlative information among fragment ions in a tandem mass spectrum can be modeled to dramatically reduce the stochastic mismatches. The experiment on the real spectra dataset shows a significant reduction of 10% in the error rate as compared to a common linear similarity function.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yan Fu
    • 1
    • 2
  • Qiang Yang
    • 3
  • Charles X. Ling
    • 4
  • Haipeng Wang
    • 1
  • Dequan Li
    • 1
  • Ruixiang Sun
    • 2
  • Hu Zhou
    • 5
  • Rong Zeng
    • 5
  • Yiqiang Chen
    • 1
  • Simin He
    • 1
  • Wen Gao
    • 1
    • 2
  1. 1.Institute of Computing TechnologyChinese Academy of SciencesBeijingChina
  2. 2.Graduate School of Chinese Academy of SciencesBeijingChina
  3. 3.Department of Computer ScienceHong Kong University of Science and TechnologyKowloon, Hong Kong
  4. 4.Department of Computer ScienceThe University of Western OntarioLondonCanada
  5. 5.Research Center for Proteome Analysis, Key Lab of Proteomics, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina

Personalised recommendations