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International Workshop on Algorithms in Bioinformatics

WABI 2002: Algorithms in Bioinformatics pp 1–9Cite as

Simultaneous Relevant Feature Identification and Classification in High-Dimensional Spaces

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2452))

Abstract

Molecular profiling technologies monitor thousands of transcripts, proteins, metabolites or other species concurrently in biological samples of interest. Given two-class, high-dimensional profiling data, nominal Liknon [4] is a specific implementation of a methodology for performing simultaneous relevant feature identification and classification. It exploits the well-known property that minimizing an l 1 norm (via linear programming) yields a sparse hyperplane [15],[26],[2],[8],[17]. This work (i) examines computational, software and practical issues required to realize nominal Liknon, (ii) summarizes results from its application to five real world data sets, (iii) outlines heuristic solutions to problems posed by domain experts when interpreting the results and (iv) defines some future directions of the research.

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Author information

Authors and Affiliations

  1. Life Sciences Division, Lawrence Berkeley National Laboratory, 94720, Berkeley, CA

    L. R. Grate & I. S. Mian

  2. Department of EECS, University of California Berkeley, 94720, Berkeley, CA

    C. Bhattacharyya & M. I. Jordan

  3. Department of Statistics, University of California Berkeley, 94720, Berkeley, CA

    C. Bhattacharyya & M. I. Jordan

Authors
  1. L. R. Grate
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  2. C. Bhattacharyya
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  3. M. I. Jordan
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  4. I. S. Mian
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Editor information

Editors and Affiliations

  1. IMIM-UPF-CRG, Dr. Aiguader 80, 08003, Barcelona, Spain

    Roderic Guigó

  2. Department of Computer Science, University of California, 95616, Davis, CA, USA

    Dan Gusfield

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© 2002 Springer-Verlag Berlin Heidelberg

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Grate, L.R., Bhattacharyya, C., Jordan, M.I., Mian, I.S. (2002). Simultaneous Relevant Feature Identification and Classification in High-Dimensional Spaces. In: Guigó, R., Gusfield, D. (eds) Algorithms in Bioinformatics. WABI 2002. Lecture Notes in Computer Science, vol 2452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45784-4_1

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  • DOI: https://doi.org/10.1007/3-540-45784-4_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44211-0

  • Online ISBN: 978-3-540-45784-8

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