Reconstruction of metabolic association networks using high-throughput mass spectrometry data

Imhoi Koo, Xiang Zhang, Seongho Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Graphical Gaussian model (GGM) has been widely used in genomics and proteomics to infer biological association networks, but the relative performances of various GGM-based methods are still unclear in metabolomics. The association between two nodes of GGM is calculated by partial correlation as a measure of conditional independence. To estimate the partial correlations with small sample size and large variables, two approaches have been introduced, which are arithmetic mean-based and geometric mean-based methods. In this study, we investigated the effects of these two approaches on constructing association metabolite networks and then compared their performances using partial least squares regression and principal component regression along with shrinkage covariance estimate as a reference. These approaches then are applied to simulated data and real metabolomics data.

Original languageEnglish (US)
Title of host publicationIntelligent Computing Technology - 8th International Conference, ICIC 2012, Proceedings
Pages160-167
Number of pages8
DOIs
StatePublished - Aug 28 2012
Event8th International Conference on Intelligent Computing Technology, ICIC 2012 - Huangshan, China
Duration: Jul 25 2012Jul 29 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7389 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Intelligent Computing Technology, ICIC 2012
CountryChina
CityHuangshan
Period7/25/127/29/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Koo, I., Zhang, X., & Kim, S. (2012). Reconstruction of metabolic association networks using high-throughput mass spectrometry data. In Intelligent Computing Technology - 8th International Conference, ICIC 2012, Proceedings (pp. 160-167). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7389 LNCS). https://doi.org/10.1007/978-3-642-31588-6_21