Literature DB >> 23614579

Statistical spectroscopic tools for biomarker discovery and systems medicine.

Steven L Robinette1, John C Lindon, Jeremy K Nicholson.   

Abstract

Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

Mesh:

Substances:

Year:  2013        PMID: 23614579     DOI: 10.1021/ac4007254

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  16 in total

Review 1.  Role of Metabolomics in Traumatic Brain Injury Research.

Authors:  Stephanie M Wolahan; Daniel Hirt; Daniel Braas; Thomas C Glenn
Journal:  Neurosurg Clin N Am       Date:  2016-08-10       Impact factor: 2.509

Review 2.  Can NMR solve some significant challenges in metabolomics?

Authors:  G A Nagana Gowda; Daniel Raftery
Journal:  J Magn Reson       Date:  2015-08-18       Impact factor: 2.229

3.  Multi-tissue metabolic responses of goldfish (Carassius auratus) exposed to glyphosate-based herbicide.

Authors:  Ming-Hui Li; Hua-Dong Xu; Yan Liu; Ting Chen; Lei Jiang; Yong-Hong Fu; Jun-Song Wang
Journal:  Toxicol Res (Camb)       Date:  2016-04-15       Impact factor: 3.524

Review 4.  Applications of NMR spectroscopy to systems biochemistry.

Authors:  Teresa W-M Fan; Andrew N Lane
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2016-02-06       Impact factor: 9.795

5.  Identifying unknown metabolites using NMR-based metabolic profiling techniques.

Authors:  Isabel Garcia-Perez; Joram M Posma; Jose Ivan Serrano-Contreras; Claire L Boulangé; Queenie Chan; Gary Frost; Jeremiah Stamler; Paul Elliott; John C Lindon; Elaine Holmes; Jeremy K Nicholson
Journal:  Nat Protoc       Date:  2020-07-17       Impact factor: 13.491

6.  Extractive Ratio Analysis NMR Spectroscopy for Metabolite Identification in Complex Biological Mixtures.

Authors:  Liladhar Paudel; G A Nagana Gowda; Daniel Raftery
Journal:  Anal Chem       Date:  2019-05-14       Impact factor: 6.986

Review 7.  Multidimensional approaches to NMR-based metabolomics.

Authors:  Kerem Bingol; Rafael Brüschweiler
Journal:  Anal Chem       Date:  2013-11-22       Impact factor: 6.986

Review 8.  Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

Authors:  Jennifer L Wilson; Russ B Altman
Journal:  Exp Biol Med (Maywood)       Date:  2017-12-03

9.  Development of an NMR-Based Platform for the Direct Structural Annotation of Complex Natural Products Mixtures.

Authors:  Joseph M Egan; Jeffrey A van Santen; Dennis Y Liu; Roger G Linington
Journal:  J Nat Prod       Date:  2021-03-22       Impact factor: 4.050

Review 10.  An overview of methods using (13)C for improved compound identification in metabolomics and natural products.

Authors:  Chaevien S Clendinen; Gregory S Stupp; Ramadan Ajredini; Brittany Lee-McMullen; Chris Beecher; Arthur S Edison
Journal:  Front Plant Sci       Date:  2015-08-25       Impact factor: 5.753

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