Journal ArticleDOI
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.read more
Citations
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Systems biology approaches to precision medicine
TL;DR: Systems Biology Approaches to Precision Medicine: Advances in Systems Biology and Precision Medicine
Journal ArticleDOI
Identification of proteins associated with development of psoriatic arthritis in peripheral blood mononuclear cells: a quantitative iTRAQ-based proteomics study.
Jie Zhu,Ling Han,Ruilai Liu,Zhenghua Zhang,Qiong Huang,Xu Fang,Ke Yang,Guiqin Huang,Zhi-Zhong Zheng,Nikhil Yawalkar,Hui Deng,Kexiang Yan +11 more
TL;DR: Wang et al. as discussed by the authors applied isobaric tags for relative and absolute quantification (iTRAQ) and LC-MS/MS to analyze the proteome profile of peripheral blood mononuclear cells (PBMCs) collected from patients with psoriasis without arthritis (PsO) and healthy controls.
Journal ArticleDOI
LFAQ: Toward Unbiased Label-Free Absolute Protein Quantification by Predicting Peptide Quantitative Factors
Cheng Chang,Zhiqiang Gao,Wantao Ying,Yan Fu,Yan Zhao,Songfeng Wu,Mengjie Li,Guibin Wang,Xiaohong Qian,Yunping Zhu,Yunping Zhu,Fuchu He +11 more
TL;DR: An algorithm for label-free absolute protein quantification, LFAQ, which can correct the biased MS intensities by using the predicted peptide quantitative factors for all identified peptides, which presented accuracy and precision superior to those of existing methods.
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Molecular classification of the placebo effect in nausea
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