HiRes - A tool for comprehensive assessment and interpretation of metabolomic data

Qi Zhao, Radka Stoyanova, Shuyan Du, Paul Sajda, Truman R. Brown

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Summary: The increasing role of metabolomics in system biology is driving the development of tools for comprehensive analysis of high-resolution NMR spectral datasets. This task is quite challenging since unlike the datasets resulting from other 'omics', a substantial preprocessing of the data is needed to allow successful identification of spectral patterns associated with relevant biological variability. HiRes is a unique stand-alone software tool that combines standard NMR spectral processing functionalities with techniques for multi-spectral dataset analysis, such as principal component analysis and non-negative matrix factorization. In addition, HiRes contains extensive abilities for data cleansing, such as baseline correction, solvent peak suppression, removal of frequency shifts owing to experimental conditions as well as auxiliary information management. Integration of these components together with multivariate analytical procedures makes HiRes very capable of addressing the challenges for assessment and interpretation of large metabolomic datasets, greatly simplifying this otherwise lengthy and difficult process and assuring optimal information retrieval.

Original languageEnglish (US)
Pages (from-to)2562-2564
Number of pages3
JournalBioinformatics
Volume22
Issue number20
DOIs
StatePublished - Oct 1 2006
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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