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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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The Perseus computational platform for comprehensive analysis of (prote)omics data.

TL;DR: The Perseus software platform was developed to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data and it is anticipated that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ

TL;DR: A new intensity determination and normalization procedure called MaxLFQ is developed that is fully compatible with any peptide or protein separation prior to LC-MS analysis, which accurately detects the mixing ratio over the entire protein expression range, with greater precision for abundant proteins.
Journal Article

Interactome networks and human disease

TL;DR: Why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease are detailed.
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Methods of integrating data to uncover genotype–phenotype interactions

TL;DR: The emerging approaches for data integration — including meta-dimensional and multi-staged analyses — which aim to deepen the understanding of the role of genetics and genomics in complex outcomes are explored.
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Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

TL;DR: This work presents CSI:FingerID, which combines fragmentation tree computation and machine learning for searching molecular structure databases using tandem MS data of small molecules, and is shown to improve on the competing methods for computational metabolite identification by a considerable margin.
References
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Journal ArticleDOI

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aPKC phosphorylates NuMA-related LIN-5 to position the mitotic spindle during asymmetric division

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Proteomic snapshot of the EGF-induced ubiquitin network

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Advancing Cell Biology Through Proteomics in Space and Time (PROSPECTS)

TL;DR: A perspective on how the proteomics field is moving beyond simply identifying proteins with high sensitivity toward providing a powerful and versatile set of assay systems for characterizing proteome dynamics and thereby creating a new “third generation” proteomics strategy that offers an indispensible tool for cell biology and molecular medicine is presented.
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