Literature DB >> 18541471

Experimental and computational approaches to quantitative proteomics: status quo and outlook.

Alexandre Panchaud1, Michael Affolter, Philippe Moreillon, Martin Kussmann.   

Abstract

Proteomics has come a long way from the initial qualitative analysis of proteins present in a given sample at a given time ("cataloguing") to large-scale characterization of proteomes, their interactions and dynamic behavior. Originally enabled by breakthroughs in protein separation and visualization (by two-dimensional gels) and protein identification (by mass spectrometry), the discipline now encompasses a large body of protein and peptide separation, labeling, detection and sequencing tools supported by computational data processing. The decisive mass spectrometric developments and most recent instrumentation news are briefly mentioned accompanied by a short review of gel and chromatographic techniques for protein/peptide separation, depletion and enrichment. Special emphasis is placed on quantification techniques: gel-based, and label-free techniques are briefly discussed whereas stable-isotope coding and internal peptide standards are extensively reviewed. Another special chapter is dedicated to software and computing tools for proteomic data processing and validation. A short assessment of the status quo and recommendations for future developments round up this journey through quantitative proteomics.

Mesh:

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Year:  2007        PMID: 18541471     DOI: 10.1016/j.jprot.2007.12.001

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  20 in total

1.  LC-MS Based Detection of Differential Protein Expression.

Authors:  Leepika Tuli; Habtom W Ressom
Journal:  J Proteomics Bioinform       Date:  2009-10-02

2.  A novel alignment method and multiple filters for exclusion of unqualified peptides to enhance label-free quantification using peptide intensity in LC-MS/MS.

Authors:  Xianyin Lai; Lianshui Wang; Haixu Tang; Frank A Witzmann
Journal:  J Proteome Res       Date:  2011-09-21       Impact factor: 4.466

3.  Enhanced information output from shotgun proteomics data by protein quantification and peptide quality control (PQPQ).

Authors:  Jenny Forshed; Henrik J Johansson; Maria Pernemalm; Rui M M Branca; Annsofi Sandberg; Janne Lehtiö
Journal:  Mol Cell Proteomics       Date:  2011-07-06       Impact factor: 5.911

4.  Quantitative analysis of p53 expression in human normal and cancer tissue microarray with global normalization method.

Authors:  Halliday A Idikio
Journal:  Int J Clin Exp Pathol       Date:  2011-06-15

5.  A label-free differential quantitative mass spectrometry method for the characterization and identification of protein changes during citrus fruit development.

Authors:  Ehud Katz; Mario Fon; Richard A Eigenheer; Brett S Phinney; Joseph N Fass; Dawei Lin; Avi Sadka; Eduardo Blumwald
Journal:  Proteome Sci       Date:  2010-12-16       Impact factor: 2.480

6.  Shotgun proteomics in neuroscience.

Authors:  Lujian Liao; Daniel B McClatchy; John R Yates
Journal:  Neuron       Date:  2009-07-16       Impact factor: 17.173

7.  Highlights on the capacities of "Gel-based" proteomics.

Authors:  François Chevalier
Journal:  Proteome Sci       Date:  2010-04-28       Impact factor: 2.480

8.  Improved detection of quantitative differences using a combination of spectral counting and MS/MS total ion current.

Authors:  Dana M Freund; Jessica E Prenni
Journal:  J Proteome Res       Date:  2013-03-12       Impact factor: 4.466

9.  Segmentation of precursor mass range using "tiling" approach increases peptide identifications for MS1-based label-free quantification.

Authors:  Catherine E Vincent; Gregory K Potts; Arne Ulbrich; Michael S Westphall; James A Atwood; Joshua J Coon; D Brent Weatherly
Journal:  Anal Chem       Date:  2013-02-12       Impact factor: 6.986

10.  Quantitative proteomic analysis of human substantia nigra in Alzheimer's disease, Huntington's disease and Multiple sclerosis.

Authors:  Sheng Chen; Frances Fangjia Lu; Philip Seeman; Fang Liu
Journal:  Neurochem Res       Date:  2012-08-28       Impact factor: 3.996

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