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Open AccessJournal ArticleDOI

A Quantitative Spatial Proteomics Analysis of Proteome Turnover in Human Cells

TLDR
A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization, suggesting a general mechanism whereby their assembly is controlled in a different sub cellular location to their main site of function.
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This article is published in Molecular & Cellular Proteomics.The article was published on 2012-03-01 and is currently open access. It has received 368 citations till now. The article focuses on the topics: Stable isotope labeling by amino acids in cell culture & Proteome.

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Citations
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On the Dependency of Cellular Protein Levels on mRNA Abundance.

TL;DR: It is concluded that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.
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A census of human RNA-binding proteins.

TL;DR: This work presents a census of 1,542 manually curated RBPs that are analysed for their interactions with different classes of RNA, their evolutionary conservation, their abundance and their tissue-specific expression, a critical step towards the comprehensive characterization of proteins involved in human RNA metabolism.
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Protein Analysis by Shotgun/Bottom-up Proteomics

TL;DR: The progress of proteomics has been driven by the development of new technologies for peptide/protein separation, mass spectrometry analysis, isotope labeling for quantification, and bioinformatics data analysis.
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Ribosome biogenesis in cancer: new players and therapeutic avenues

TL;DR: The most recent findings that provide new insights into the molecular basis of ribosome biogenesis in cancer are highlighted and the perspective on how these observations present opportunities for the design of new targeted cancer treatments is offered.
References
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Journal ArticleDOI

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

TL;DR: By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

TL;DR: MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data, detects peaks, isotope clusters and stable amino acid isotope–labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space and achieves mass accuracy in the p.p.b. range.
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DAVID: Database for Annotation, Visualization, and Integrated Discovery

TL;DR: DAMID is a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries that assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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Mass Spectrometric Sequencing of Proteins from Silver-Stained Polyacrylamide Gels

TL;DR: Silver staining allows a substantial shortening of sample preparation time and may, therefore, be preferable over Coomassie staining, and this work removes a major obstacle to the low-level sequence analysis of proteins separated on polyacrylamide gels.
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Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

TL;DR: SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system and is applied to the relative quantitation of changes in protein expression during the process of muscle cell differentiation.
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