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Next-generation proteomics: towards an integrative view of proteome dynamics

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TLDR
MS-based proteomics is starting to mature and to deliver through a combination of developments in instrumentation, sample preparation and computational analysis, and to highlight recent applications.
Abstract
Next-generation sequencing allows the analysis of genomes, including those representing disease states. However, the causes of most disorders are multifactorial, and systems-level approaches, including the analysis of proteomes, are required for a more comprehensive understanding. The proteome is extremely multifaceted owing to splicing and protein modifications, and this is further amplified by the interconnectivity of proteins into complexes and signalling networks that are highly divergent in time and space. Proteome analysis heavily relies on mass spectrometry (MS). MS-based proteomics is starting to mature and to deliver through a combination of developments in instrumentation, sample preparation and computational analysis. Here we describe this emerging next generation of proteomics and highlight recent applications.

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Impact of Amidination on Peptide Fragmentation and Identification in Shotgun Proteomics

TL;DR: A supervised postprocessing algorithm is developed to exploit the unique and highly reproducible fragmentation properties of SMTA-labeled peptides, such as the strong propensity for forming b1 fragment ions, to modify the scoring of peptide-spectrum pairs and improve peptide identification.
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Three-dimensional ordered titanium dioxide-zirconium dioxide film-based microfluidic device for efficient on-chip phosphopeptide enrichment.

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification.

TL;DR: A deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes is introduced.
References
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