Results 171 to 180 of about 17,544 (219)

Identification of candidate genes and proteins for tasseling stage drought tolerance through integrated transcriptomic and proteomic analysis approach in maize. [PDF]

BMC Plant Biol
Liu S, Shi H, Yan L, Jiang C, Zhao H, Lu H, Li H, Wang S, Huang Z.   +8 more
europepmc   +1 more source

Overexpression of Transferrin Receptor in Esophageal Squamous Cell Cancer Suggests Poor Prognosis and Potential Therapy. [PDF]

Cancer Sci
Ikenaga N, Takahashi T, Tanaka K, Serada S, Fujimoto M, Momose K, Yamashita K, Makino T, Saito T, Yamamoto K, Kurokawa Y, Nakajima K, Fujii T, Morii E, Naka T, Eguchi H, Doki Y.   +16 more
europepmc   +1 more source

Rebalancing the seed proteome following deletion of vicilin-related genes in pea (Pisum sativum L.). [PDF]

J Exp Bot
Rayner T, Saalbach G, Vickers M, Paajanen P, Martins C, Wouters RHM, Chinoy C, Mulholland F, Bal M, Isaac P, Novak P, Macas J, Ellis N, Steuernagel B, Domoney C.   +14 more
europepmc   +1 more source

iTRAQ protein quantification: A quality‐controlled workflow

Proteomics, 2011
AbstractReporter ion‐based methods are among the major techniques to quantify peptides and proteins. Two main labels, tandem mass tag (TMT) and iTRAQ, are widely used by the proteomics community. They are, however, often applied as out‐of‐the‐box methods, without thorough quality control.
Albert Sickmann, René Zahedi, Marc Vaudel   +2 more
exaly   +4 more sources

A Statistical Model for iTRAQ Data Analysis [PDF]

Journal of Proteome Research, 2008
We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change.
Kevin Schey, Jeanette Eckel-Passow, Elizabeth Hill   +2 more
exaly   +3 more sources

Shotgun proteomics using the iTRAQ isobaric tags [PDF]

Briefings in Functional Genomics & Proteomics, 2006
Shotgun proteomic methods involving isobaric tagging of peptides enable high-throughput proteomic analysis. iTRAQ reagents allow simultaneous identification and quantitation of proteins in four different samples using tandem mass spectrometry (MS). In this article, we provide a brief description of proteome analysis using iTRAQ reagents and review the ...
Kelvin H Lee, Leila H Choe
exaly   +3 more sources

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Phosphoproteomics Using iTRAQ

2011
The identification of phosphorylation on proteins has become practicable for many laboratories in recent years, largely due to improvements in mass spectrometry (MS) and the development of methods to selectively enrich for phosphorylated peptides and proteins.
Alexandra M E, Jones, Thomas S, Nühse
openaire   +2 more sources

Plant iTRAQ‐Based Proteomics

Current Protocols in Plant Biology, 2017
AbstractWe present a simple one‐pot extraction protocol, which rapidly isolates hydrophilic metabolites, lipids, and proteins from the same pulverized plant sample. Also detailed is a global plant proteomics sample preparation method utilizing iTRAQ multiplexing reagents that enables deep proteome coverage due to the use of HPLC fractionation of the ...
Pubudu P. Handakumbura, Kim K. Hixson, Samuel O. Purvine, Christer Jansson, Ljiljana Paša‐Tolić   +4 more
openaire   +1 more source

Dissecting the iTRAQ Data Analysis

2016
In the era of large-scale quantitative biology, mass spectrometry-based quantitative proteomics is progressively becoming indispensable for gaining insights into the biological systems at molecular level. Various quantitative study designs rely on chemical tagging approaches to study disease, stress, or drug response and temporal studies aiming at ...
Suruchi, Aggarwal, Amit Kumar, Yadav
openaire   +2 more sources

Quantification of Proteins by iTRAQ

2010
Protein relative quantification is a key facet of many proteomics experiments. Several methods exist for this type of work, some of which are described elsewhere in this volume. In this chapter we will describe the use of isobaric tags for relative and absolute quantification (iTRAQ).
openaire   +4 more sources