Literature DB >> 15221754

Assessing factors for reliable quantitative proteomics based on two-dimensional gel electrophoresis.

Julie Fiévet1, Christine Dillmann, Gilles Lagniel, Marlène Davanture, Luc Negroni, Jean Labarre, Dominique de Vienne.   

Abstract

We statistically analysed various factors to get accurate estimates of protein quantities from two-dimensional gels. Yeast proteins were labelled with (35)S or stained with Coomassie Brilliant Blue G-250, and spots were automatically quantified with software packages Kepler, ImageQuaNT, Melanie 3.0 and Progenesis. The different software packages proved to have very similar performances. With (35)S-labelled actin spot as a reference, we studied the staining efficiency of colloidal Coomassie blue as a function of amino acid composition of the protein, and derived an equation to estimate the number of molecules per cell from blue-stained proteins. Absolute quantification of most glycolytic enzymes was carried out in two yeast strains.

Entities:  

Mesh：

Substances：

Year:  2004        PMID： 15221754     DOI： 10.1002/pmic.200300731

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


  9 in total

1.  Addressing accuracy and precision issues in iTRAQ quantitation.

Authors:  Natasha A Karp; Wolfgang Huber; Pawel G Sadowski; Philip D Charles; Svenja V Hester; Kathryn S Lilley
Journal:  Mol Cell Proteomics       Date:  2010-04-10       Impact factor: 5.911

2.  Simplified modelling of metabolic pathways for flux prediction and optimization: lessons from an in vitro reconstruction of the upper part of glycolysis.

Authors:  Julie B Fiévet; Christine Dillmann; Gilles Curien; Dominique de Vienne
Journal:  Biochem J       Date:  2006-06-01       Impact factor: 3.857

3.  ABRF-PRG07: advanced quantitative proteomics study.

Authors:  Arnold M Falick; William S Lane; Kathryn S Lilley; Michael J MacCoss; Brett S Phinney; Nicholas E Sherman; Susan T Weintraub; H Ewa Witkowska; Nathan A Yates
Journal:  J Biomol Tech       Date:  2011-04

4.  Linking post-translational modifications and variation of phenotypic traits.

Authors:  Warren Albertin; Philippe Marullo; Marina Bely; Michel Aigle; Aurélie Bourgais; Olivier Langella; Thierry Balliau; Didier Chevret; Benoît Valot; Telma da Silva; Christine Dillmann; Dominique de Vienne; Delphine Sicard
Journal:  Mol Cell Proteomics       Date:  2012-12-27       Impact factor: 5.911

5.  Statistical model to analyze quantitative proteomics data obtained by 18O/16O labeling and linear ion trap mass spectrometry: application to the study of vascular endothelial growth factor-induced angiogenesis in endothelial cells.

Authors:  Inmaculada Jorge; Pedro Navarro; Pablo Martínez-Acedo; Estefanía Núñez; Horacio Serrano; Arántzazu Alfranca; Juan Miguel Redondo; Jesús Vázquez
Journal:  Mol Cell Proteomics       Date:  2009-01-29       Impact factor: 5.911

Review 6.  Proteomics of plant pathogenic fungi.

Authors:  Raquel González-Fernández; Elena Prats; Jesús V Jorrín-Novo
Journal:  J Biomed Biotechnol       Date:  2010-05-27

7.  Systemic properties of metabolic networks lead to an epistasis-based model for heterosis.

Authors:  Julie B Fiévet; Christine Dillmann; Dominique de Vienne
Journal:  Theor Appl Genet       Date:  2009-11-15       Impact factor: 5.699

8.  PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios.

Authors:  Chris Bauer; Frank Kleinjung; Dorothea Rutishauser; Christian Panse; Alexandra Chadt; Tanja Dreja; Hadi Al-Hasani; Knut Reinert; Ralph Schlapbach; Johannes Schuchhardt
Journal:  BMC Bioinformatics       Date:  2012-02-16       Impact factor: 3.169

9.  Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations.

Authors:  Julie B Fiévet; Thibault Nidelet; Christine Dillmann; Dominique de Vienne
Journal:  Front Genet       Date:  2018-05-15       Impact factor: 4.599
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.