Literature DB >> 14630657

Metabolomics spectral formatting, alignment and conversion tools (MSFACTs).

Anthony L Duran1, Jian Yang, Liangjiang Wang, Lloyd W Sumner.   

Abstract

MOTIVATION: The amplified interest in metabolic profiling has generated the need for additional tools to assist in the rapid analysis of complex data sets.
RESULTS: A new program; metabolomics spectral formatting, alignment and conversion tools, (MSFACTs) is described here for the automated import, reformatting, alignment, and export of large chromatographic data sets to allow more rapid visualization and interrogation of metabolomic data. MSFACTs incorporates two tools: one for the alignment of integrated chromatographic peak lists and another for extracting information from raw chromatographic ASCII formatted data files. MSFACTs is illustrated in the processing of GC/MS metabolomic data from different tissues of the model legume plant, Medicago truncatula. The results document that various tissues such as roots, stems, and leaves from the same plant can be easily differentiated based on metabolite profiles. Further, similar types of tissues within the same plant, such as the first to eleventh internodes of stems, could also be differentiated based on metabolite profiles. AVAILABILITY: Freely available upon request for academic and non-commercial use. Commercial use is available through licensing agreement http://www.noble.org/PlantBio/MS/MSFACTs/MSFACTs.html.

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Year:  2003        PMID: 14630657     DOI: 10.1093/bioinformatics/btg315

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


  35 in total

1.  Global metabolic profiling procedures for urine using UPLC-MS.

Authors:  Elizabeth J Want; Ian D Wilson; Helen Gika; Georgios Theodoridis; Robert S Plumb; John Shockcor; Elaine Holmes; Jeremy K Nicholson
Journal:  Nat Protoc       Date:  2010-06       Impact factor: 13.491

2.  Combining genetic diversity, informatics and metabolomics to facilitate annotation of plant gene function.

Authors:  Takayuki Tohge; Alisdair R Fernie
Journal:  Nat Protoc       Date:  2010-06-10       Impact factor: 13.491

3.  PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools.

Authors:  Sean O'Callaghan; David P De Souza; Andrew Isaac; Qiao Wang; Luke Hodkinson; Moshe Olshansky; Tim Erwin; Bill Appelbe; Dedreia L Tull; Ute Roessner; Antony Bacic; Malcolm J McConville; Vladimir A Likić
Journal:  BMC Bioinformatics       Date:  2012-05-30       Impact factor: 3.169

Review 4.  Metabolomics and its role in understanding cellular responses in plants.

Authors:  Ritu Bhalla; Kothandaraman Narasimhan; Sanjay Swarup
Journal:  Plant Cell Rep       Date:  2005-11-16       Impact factor: 4.570

5.  Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum.

Authors:  Anders Nordström; Grace O'Maille; Chuan Qin; Gary Siuzdak
Journal:  Anal Chem       Date:  2006-05-15       Impact factor: 6.986

6.  Highly-parallel metabolomics approaches using LC-MS for pharmaceutical and environmental analysis.

Authors:  Sunil Bajad; Vladimir Shulaev
Journal:  Trends Analyt Chem       Date:  2007-06-01       Impact factor: 12.296

7.  Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst.

Authors:  Jianguo Xia; David S Wishart
Journal:  Nat Protoc       Date:  2011-05-05       Impact factor: 13.491

8.  Lotus japonicus metabolic profiling. Development of gas chromatography-mass spectrometry resources for the study of plant-microbe interactions.

Authors:  Guilhem G Desbrosses; Joachim Kopka; Michael K Udvardi
Journal:  Plant Physiol       Date:  2005-03-04       Impact factor: 8.340

9.  Hydrocarbon phenotyping of algal species using pyrolysis-gas chromatography mass spectrometry.

Authors:  Dinesh K Barupal; Tobias Kind; Shankar L Kothari; Do Yup Lee; Oliver Fiehn
Journal:  BMC Biotechnol       Date:  2010-05-21       Impact factor: 2.563

10.  The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

Authors:  Adam J Carroll; Murray R Badger; A Harvey Millar
Journal:  BMC Bioinformatics       Date:  2010-07-14       Impact factor: 3.169

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