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John Rush

Researcher at Cell Signaling Technology

Publications -  75
Citations -  16699

John Rush is an academic researcher from Cell Signaling Technology. The author has contributed to research in topics: Phosphorylation & Receptor tyrosine kinase. The author has an hindex of 43, co-authored 74 publications receiving 15600 citations. Previous affiliations of John Rush include Institute for Systems Biology.

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Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS

TL;DR: The AQUA strategy was used to quantify low abundance yeast proteins involved in gene silencing, quantitatively determine the cell cycle-dependent phosphorylation of Ser-1126 of human separase protein, and identify kinases capable of phosphorylating Ser-1501 of separase in an in vitro kinase assay.
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A probability-based approach for high-throughput protein phosphorylation analysis and site localization.

TL;DR: A large-scale phosphorylation data set is provided with a measured error rate as determined by the target-decoy approach, an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs) is demonstrated, and a probability-based score is presented, the Ascore, that measures the probability of correct phosphorylated site localization based on the presence and intensity of site-determining ions in MS/MS spectra.
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Systematic and Quantitative Assessment of the Ubiquitin-Modified Proteome

TL;DR: The human ubiquitin-modified proteome is characterized using a monoclonal antibody that recognizes diglycine (diGly)-containing isopeptides following trypsin digestion and it is demonstrated that quantitative diGly proteomics can be utilized to identify substrates for cullin-RING ubiquitIn ligases.
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Immunoaffinity profiling of tyrosine phosphorylation in cancer cells

TL;DR: Applying this approach to several cell systems, including cancer cell lines, shows it can be used to identify activated protein kinases and their phosphorylated substrates without prior knowledge of the signaling networks that are activated, a first step in profiling normal and oncogenic signaling networks.