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Open AccessJournal ArticleDOI

MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data

TLDR
A new generation of a popular open-source data processing toolbox, MZmine 2 is introduced, suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
Abstract
Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/ . The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.

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Lipidomics in biomedical research-practical considerations

TL;DR: The key challenges ahead in the field of lipidomics in medical research lie in the development of experimental protocols and in silico techniques needed to study lipidomes at the systems level.
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Dose-dependent metabolic alterations in human cells exposed to gamma irradiation

TL;DR: The results suggest that MS-based metabolite profiling of γ-radiation-exposed human cells provides insight into the global metabolic alterations in these cells.
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Combined Markers to Assess Meat Intake—Human Metabolomic Studies of Discovery and Validation

TL;DR: New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.
Journal ArticleDOI

A new processing scheme for ultra-high resolution direct infusion mass spectrometry data

TL;DR: In this article, a new processing scheme is introduced implementing filtering methods based on element assignment, instrumental error, and blank subtraction, which allows both positive and negative direct infusion electrospray ionisation (ESI) and atmospheric pressure photoionisation (APPI) acquisition with the same programs.
Journal ArticleDOI

MultiAlign: a multiple LC-MS analysis tool for targeted omics analysis.

TL;DR: MultiAlign is an efficient software package for finding similar analytes across multiple liquid chromatography-mass spectrometry feature maps, as demonstrated here for both proteomics and metabolomics experiments.
References
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TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Journal ArticleDOI

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

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Probability-based protein identification by searching sequence databases using mass spectrometry data.

TL;DR: A new computer program, Mascot, is presented, which integrates all three types of search for protein identification by searching a sequence database using mass spectrometry data, and the scoring algorithm is probability based.
Journal ArticleDOI

Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting

TL;DR: Locally weighted regression as discussed by the authors is a way of estimating a regression surface through a multivariate smoothing procedure, fitting a function of the independent variables locally and in a moving fashion analogous to how a moving average is computed for a time series.
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METLIN: a metabolite mass spectral database.

TL;DR: METLIN includes an annotated list of known metabolite structural information that is easily cross-correlated with its catalogue of high-resolution Fourier transform mass spectrometry (FTMS) spectra, tandem mass spectrumetry (MS/MS) Spectra, and LC/MS data.
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