Literature DB >> 21243637

Less label, more free: approaches in label-free quantitative mass spectrometry.

Karlie A Neilson1, Naveid A Ali, Sridevi Muralidharan, Mehdi Mirzaei, Michael Mariani, Gariné Assadourian, Albert Lee, Steven C van Sluyter, Paul A Haynes.   

Abstract

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.
Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mesh:

Year:  2011        PMID: 21243637     DOI: 10.1002/pmic.201000553

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  197 in total

1.  Absolute quantification of the glycolytic pathway in yeast: deployment of a complete QconCAT approach.

Authors:  Kathleen M Carroll; Deborah M Simpson; Claire E Eyers; Christopher G Knight; Philip Brownridge; Warwick B Dunn; Catherine L Winder; Karin Lanthaler; Pinar Pir; Naglis Malys; Douglas B Kell; Stephen G Oliver; Simon J Gaskell; Robert J Beynon
Journal:  Mol Cell Proteomics       Date:  2011-09-19       Impact factor: 5.911

2.  Global kinetic analysis of proteolysis via quantitative targeted proteomics.

Authors:  Nicholas J Agard; Sami Mahrus; Jonathan C Trinidad; Aenoch Lynn; Alma L Burlingame; James A Wells
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-23       Impact factor: 11.205

3.  DeMix-Q: Quantification-Centered Data Processing Workflow.

Authors:  Bo Zhang; Lukas Käll; Roman A Zubarev
Journal:  Mol Cell Proteomics       Date:  2016-01-04       Impact factor: 5.911

4.  QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues.

Authors:  Harsha P Gunawardena; Jonathon O'Brien; John A Wrobel; Ling Xie; Sherri R Davies; Shunqiang Li; Matthew J Ellis; Bahjat F Qaqish; Xian Chen
Journal:  Mol Cell Proteomics       Date:  2015-11-23       Impact factor: 5.911

Review 5.  A Biologist's Field Guide to Multiplexed Quantitative Proteomics.

Authors:  Corey E Bakalarski; Donald S Kirkpatrick
Journal:  Mol Cell Proteomics       Date:  2016-02-12       Impact factor: 5.911

6.  CD39 is a promising therapeutic antibody target for the treatment of soft tissue sarcoma.

Authors:  Gregory M Hayes; Belinda Cairns; Zoia Levashova; Lawrence Chinn; Myra Perez; Jan-Willem Theunissen; Sindy Liao-Chan; Abel Bermudez; Mark R Flory; Karl J Schweighofer; Edward H van der Horst
Journal:  Am J Transl Res       Date:  2015-06-15       Impact factor: 4.060

Review 7.  The spectra count label-free quantitation in cancer proteomics.

Authors:  Weidong Zhou; Lance A Liotta; Emanuel F Petricoin
Journal:  Cancer Genomics Proteomics       Date:  2012 May-Jun       Impact factor: 4.069

Review 8.  Quantification of histone modifications using ¹⁵N metabolic labeling.

Authors:  Chunchao Zhang; Yifan Liu; Philip C Andrews
Journal:  Methods       Date:  2013-02-27       Impact factor: 3.608

9.  Assessing the partners of the RBP9-mRNP complex in Trypanosoma cruzi using shotgun proteomics and RNA-seq.

Authors:  Helisa Helena Wippel; Alexandre Haruo Inoue; Newton Medeiros Vidal; Jimena Ferreira da Costa; Bruna Hilzendeger Marcon; Bruno Accioly Alves Romagnoli; Marlon Dias Mariano Santos; Paulo Costa Carvalho; Samuel Goldenberg; Lysangela Ronalte Alves
Journal:  RNA Biol       Date:  2018-09-10       Impact factor: 4.652

10.  Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients.

Authors:  Chengjian Tu; Wilfrido Mojica; Robert M Straubinger; Jun Li; Shichen Shen; Miao Qu; Lei Nie; Rick Roberts; Bo An; Jun Qu
Journal:  Proteomics Clin Appl       Date:  2017-01-20       Impact factor: 3.494

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