Literature DB >> 21551139

MPEA--metabolite pathway enrichment analysis.

Matti Kankainen1, Peddinti Gopalacharyulu, Liisa Holm, Matej Oresic.   

Abstract

UNLABELLED: We present metabolite pathway enrichment analysis (MPEA) for the visualization and biological interpretation of metabolite data at the system level. Our tool follows the concept of gene set enrichment analysis (GSEA) and tests whether metabolites involved in some predefined pathway occur towards the top (or bottom) of a ranked query compound list. In particular, MPEA is designed to handle many-to-many relationships that may occur between the query compounds and metabolite annotations. For a demonstration, we analysed metabolite profiles of 14 twin pairs with differing body weights. MPEA found significant pathways from data that had no significant individual query compounds, its results were congruent with those discovered from transcriptomics data and it detected more pathways than the competing metabolic pathway method did. AVAILABILITY: The web server and source code of MPEA are available at http://ekhidna.biocenter.helsinki.fi/poxo/mpea/.

Entities:  

Mesh:

Year:  2011        PMID: 21551139     DOI: 10.1093/bioinformatics/btr278

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  32 in total

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Authors:  Matej Oresic
Journal:  Rev Diabet Stud       Date:  2012-12-28

2.  Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.

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Journal:  Curr Metabolomics       Date:  2013-01-01

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Journal:  Nat Chem Biol       Date:  2014-02-09       Impact factor: 15.040

4.  Systems biology analysis reveals role of MDM2 in diabetic nephropathy.

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Journal:  JCI Insight       Date:  2016-10-20

5.  Reconstruction and analysis of correlation networks based on GC-MS metabolomics data for young hypertensive men.

Authors:  Le Wang; Entai Hou; Lijun Wang; Yanjun Wang; Lingjian Yang; Xiaohui Zheng; Guangqi Xie; Qiong Sun; Mingyu Liang; Zhongmin Tian
Journal:  Anal Chim Acta       Date:  2014-11-11       Impact factor: 6.558

6.  Glutamine-dependent signaling controls pluripotent stem cell fate.

Authors:  Vivian Lu; Irena J Roy; Alejandro Torres; James H Joly; Fasih M Ahsan; Nicholas A Graham; Michael A Teitell
Journal:  Dev Cell       Date:  2022-02-24       Impact factor: 12.270

Review 7.  Review: toxicometabolomics.

Authors:  Mounir Bouhifd; Thomas Hartung; Helena T Hogberg; Andre Kleensang; Liang Zhao
Journal:  J Appl Toxicol       Date:  2013-05-30       Impact factor: 3.446

8.  Pathway-Activity Likelihood Analysis and Metabolite Annotation for Untargeted Metabolomics Using Probabilistic Modeling.

Authors:  Ramtin Hosseini; Neda Hassanpour; Li-Ping Liu; Soha Hassoun
Journal:  Metabolites       Date:  2020-05-03

9.  Translational biomarker discovery in clinical metabolomics: an introductory tutorial.

Authors:  Jianguo Xia; David I Broadhurst; Michael Wilson; David S Wishart
Journal:  Metabolomics       Date:  2012-12-04       Impact factor: 4.290

10.  Metabolome in progression to Alzheimer's disease.

Authors:  M Orešič; T Hyötyläinen; S-K Herukka; M Sysi-Aho; I Mattila; T Seppänan-Laakso; V Julkunen; P V Gopalacharyulu; M Hallikainen; J Koikkalainen; M Kivipelto; S Helisalmi; J Lötjönen; H Soininen
Journal:  Transl Psychiatry       Date:  2011-12-13       Impact factor: 6.222

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