ArticleBMC bioinformatics2011
AMDORAP: non-targeted metabolic profiling based on high-resolution LC-MS.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Mining plant metabolomes: Methods, applications, and perspectives.Plant communications · 2021Review
- The metaRbolomics Toolbox in Bioconductor and beyond.Metabolites · 2019Review
- Comparative metabolic profiling ofHorticulture research · 2019Article
- Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics.International journal of molecular sciences · 2016Review
- Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach.Bioinformatics (Oxford, England) · 2014Article
- Sum of the parts: mass spectrometry-based metabolomics.Biochemistry · 2013Review
- Hybrid feature detection and information accumulation using high-resolution LC-MS metabolomics data.Journal of proteome research · 2013Article
- Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology.Computational and structural biotechnology journal · 2013Review
- Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.Current Metabolomics · 2013Article
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Authors and funding
4 authors.
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Abstract
backgroundLiquid chromatography-mass spectrometry (LC-MS) utilizing the high-resolution power of an orbitrap is an important analytical technique for both metabolomics and proteomics. Most important feature of the orbitrap is excellent mass accuracy. Thus, it is necessary to convert raw data to accurate and reliable m/z values for metabolic fingerprinting by high-resolution LC-MS.
resultsIn the present study, we developed a novel, easy-to-use and straightforward m/z detection method, AMDORAP. For assessing the performance, we used real biological samples, Bacillus subtilis strains 168 and MGB874, in the positive mode by LC-orbitrap. For 14 identified compounds by measuring the authentic compounds, we compared obtained m/z values with other LC-MS processing tools. The errors by AMDORAP were distributed within ±3 ppm and showed the best performance in m/z value accuracy.
conclusionsOur method can detect m/z values of biological samples much more accurately than other LC-MS analysis tools. AMDORAP allows us to address the relationships between biological effects and cellular metabolites based on accurate m/z values. Obtaining the accurate m/z values from raw data should be indispensable as a starting point for comparative LC-orbitrap analysis. AMDORAP is freely available under an open-source license at http://amdorap.sourceforge.net/.
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