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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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Functions of maize genes encoding pyruvate phosphate dikinase in developing endosperm.

TL;DR: It is shown that PPDK deficiency in isolation causes the negative phenotype associated with reduced kernel hardness, and maize improvement may be better accomplished by targeting individual metabolic pathways determining protein and amino acid balance rather than pleiotropic regulators such as the o2 transcription factor.
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Metabolic profiling of a transgenic Caenorhabditis elegans Alzheimer model

TL;DR: Transgenic Caenorhabditis elegans was used to investigate changes in the metabolome after induced expression of amyloid-β, revealing changes in allantoin, cystathionine and tyrosine levels that argue for further use of C. elegans as a model of human pathology in the study of AD.
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Photochemical degradation of BPF, BPS and BPZ in aqueous solution: Identification of transformation products and degradation kinetics.

TL;DR: Assessment of the photochemical degradation of three common bisphenols in aqueous solution determined their degradation kinetics and characterise their transformation products, revealing the photo-Fenton process to be an effective way of removing (>90%) BPF, BPS and BPZ from aqueously samples.
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Bioactive diterpenoids impact the composition of the root-associated microbiome in maize (Zea mays).

TL;DR: The role of specialized metabolites in modulating plant-microbiome interactions often remains elusive as mentioned in this paper, however, it is known that maize (Zea mays) diterpenoid metabolites with known antifungal bioactivities also influence rhizosphere bacterial communities.
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Lipid-Pro: a computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms

TL;DR: Lipid-Pro is a software tool that supports the identification of lipids by interpreting large datasets generated by liquid chromatography--tandem mass spectrometry using the advanced data-independent acquisition mode MS(E).
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