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UPS2

Sigma-Aldrich

Proteomics Dynamic Range Standard Set

Protein Mass Spectrometry Calibration Standard

Synonym(s):

Dynamic Range Standards, Proteomics Standard Set

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About This Item

EC Number:
232-650-8
UNSPSC Code:
12161503
NACRES:
NA.24

biological source

human

Quality Level

200

form

ready-to-use solution

quality

Protein Mass Spectrometry Calibration Standard

concentration

10.6 μg/ampule protein

technique(s)

mass spectrometry (MS): suitable

shipped in

wet ice

storage temp.

−20°C

Related Categories

General description

The Proteomics Dynamic Range Standard Set is produced from a mixture of 48 individual human source or human sequence recombinant proteins, each of which has been selected to limit heterogeneous post-translational modifications (PTMs). The protein standard is formulated from 6 mixtures of 8 proteins to present a dynamic range of 5 orders of magnitude, ranging from 50 pmoles to 500 amoles. Each protein has been quantitated by amino acid analysis (AAA) prior to formulation.

Application

Proteomics Dynamic Range Standard Set has been used in the intensity-based absolute quantification (iBAQ) of E .coli proteins, embryonic stem cells (ESCs) and neuronal precursor cells (NPCs) proteomes. It has also been used as a standard to spike HeLa cells for label-free quantification.
The Proteomics Dynamic Range Standard Set can be used to standardize and/or evaluate mass spectrometric (e.g., LC-MS/MS, MALDI-TOF-MS, etc.) and electrophoretic analysis conditions prior to the analysis of complex protein samples. UPS2 can be used to bracket precious experimental data sets between runs of a known complex standard sample. This allows confirmation of the robustness of the analysis method and stability of the instrument employed. Additionally, laboratories generating or comparing mass spectrometric data derived from poorly defined samples can use UPS2 as an external reference to assist with the evaluation of results and experimental methodology.
Proteomics Dynamic Range Standard Set has been used for the quantification of dynamic range universal protein standard on Orbitrap Analyzer using all ion fragmentation. It has been used as a standard for intensity-based absolute quantification of proteins (iBAQ) in LC-MS (liquid chromatography-mass spectrometry)/MS analysis.

Kit Components Also Available Separately

Product No.
Description
SDS
  • T6567Trypsin from porcine pancreas, Proteomics Grade, BioReagent, Dimethylated 20 μgSDS

Signal Word

Danger

Hazard Statements

H315,H318,H334,H335,H360F

Hazard Classifications

Eye Dam. 1 - Repr. 1B - Resp. Sens. 1 - Skin Irrit. 2 - STOT SE 3

Target Organs

Respiratory system

Storage Class Code

6.1C - Combustible acute toxic Cat.3 / toxic compounds or compounds which causing chronic effects

Flash Point(F)

Not applicable

Flash Point(C)

Not applicable

Certificates of Analysis (COA)

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Erik Ahrné et al.
Proteomics, 13(17), 2567-2578 (2013-06-25)
There is a great interest in reliable ways to obtain absolute protein abundances at a proteome-wide scale. To this end, label-free LC-MS/MS quantification methods have been proposed where all identified proteins are assigned an estimated abundance. Several variants of this
An interaction landscape of ubiquitin signaling
Zhang X, et al.
Molecular Cell, 65(5), 941-955 (2017)
Boumediene Soufi et al.
Frontiers in microbiology, 6, 103-103 (2015-03-06)
We set out to provide a resource to the microbiology community especially with respect to systems biology based endeavors. To this end, we generated a comprehensive dataset monitoring the changes in protein expression, copy number, and post translational modifications in
Björn Schwanhäusser et al.
Nature, 473(7347), 337-342 (2011-05-20)
Gene expression is a multistep process that involves the transcription, translation and turnover of messenger RNAs and proteins. Although it is one of the most fundamental processes of life, the entire cascade has never been quantified on a genome-wide scale.
Taejoon Kwon et al.
Journal of proteome research, 10(7), 2949-2958 (2011-04-15)
Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce
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