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Application of a New Ridge Estimator of the Inverse Covariance Matrix to the Reconstruction of Gene-Gene Interaction Networks

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Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8623))

Abstract

A proper ridge estimator of the inverse covariance matrix is presented. We study the properties of this estimator in relation to other ridge-type estimators. In the context of Gaussian graphical modeling, we compare the proposed estimator to the graphical lasso. This work is a brief exposé of the technical developments in [1], focussing on applications in gene-gene interaction network reconstruction.

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References

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Author information

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, VU University medical center, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands

    Wessel N. van Wieringen & Carel F. W. Peeters

  2. Deptartment of Mathematics, VU University Amsterdam, 1081 HV, Amsterdam, The Netherlands

    Wessel N. van Wieringen

Authors
  1. Wessel N. van Wieringen
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  2. Carel F. W. Peeters
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Corresponding author

Correspondence to Wessel N. van Wieringen .

Editor information

Editors and Affiliations

  1. CUSSB, University "Vita-Salute" San Raffae, Milano, Italy

    Clelia DI Serio

  2. The Computer Laboratory, University of Cambridge, Cambridge, United Kingdom

    Pietro Liò

  3. CUSSB, Università Vita-Salute San Raffaele, Milano, Italy

    Alessandro Nonis

  4. Dipartimento di Informatica, Universitá degli Studi di Salerno, Fisciano, Salerno, Italy

    Roberto Tagliaferri

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van Wieringen, W.N., Peeters, C.F.W. (2015). Application of a New Ridge Estimator of the Inverse Covariance Matrix to the Reconstruction of Gene-Gene Interaction Networks. In: DI Serio, C., Liò, P., Nonis, A., Tagliaferri, R. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2014. Lecture Notes in Computer Science(), vol 8623. Springer, Cham. https://doi.org/10.1007/978-3-319-24462-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-24462-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24461-7

  • Online ISBN: 978-3-319-24462-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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