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

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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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Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare)

TL;DR: This is one of the first metabolomic studies to follow CRC patients in a prospective setting with repeated urine sampling over time and was able to confirm markers initially identified in case–control studies and metabolites which may represent prognostic biomarker candidates of CRC.
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The gut microbiota modulates glycaemic control and serum metabolite profiles in non-obese diabetic mice.

TL;DR: The data suggest that germ-free NOD mice have reduced glycaemic control and dysregulated immunologic and metabolic responses, which are similar to that of pre-diabetic children.
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Metabolome analysis for discovering biomarkers of gastroenterological cancer.

TL;DR: The findings of studies that attempted to discover biomarkers of gastroenterological cancer are outlined and metabolome analysis-based disease diagnosis is discussed, and mass spectrometry-based techniques have been extensively used for metabolite analysis.
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Degradation of the anticancer drug erlotinib during water chlorination: Non-targeted approach for the identification of transformation products.

TL;DR: The reactivity of the cytostatic drug erlotinib in free chlorine-containing water was investigated for the first time and a non-targeted screening approach based on the use of differential profiling tools was applied in order to reveal its potential transformation products.
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Multi-layer solid-phase extraction and evaporation-enrichment methods for polar organic chemicals from aqueous matrices.

TL;DR: This work assessed the suitability of a novel combination of well-known solid-phase extraction materials in one cartridge as well as an evaporation method for the enrichment of 26 polar model substances covering a broad range of physico-chemical properties in three different aqueous matrices.
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