Literature DB >> 20835802

Modeling experimental design for proteomics.

Jan Eriksson1, David Fenyö.   

Abstract

The complexity of proteomes makes good experimental design essential for their successful investigation. Here, we describe how proteomics experiments can be modeled and how computer simulations of these models can be used to improve experimental designs.

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Year:  2010        PMID: 20835802      PMCID: PMC3745767          DOI: 10.1007/978-1-60761-842-3_14

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  12 in total

Review 1.  Identifying the proteome: software tools.

Authors:  D Fenyö
Journal:  Curr Opin Biotechnol       Date:  2000-08       Impact factor: 9.740

Review 2.  The human plasma proteome: history, character, and diagnostic prospects.

Authors:  N Leigh Anderson; Norman G Anderson
Journal:  Mol Cell Proteomics       Date:  2002-11       Impact factor: 5.911

Review 3.  Mass spectrometry-based proteomics.

Authors:  Ruedi Aebersold; Matthias Mann
Journal:  Nature       Date:  2003-03-13       Impact factor: 49.962

4.  Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.

Authors:  Benjamin J Cargile; Jonathan L Bundy; Thaddeus W Freeman; James L Stephenson
Journal:  J Proteome Res       Date:  2004 Jan-Feb       Impact factor: 4.466

Review 5.  Informatics for protein identification by mass spectrometry.

Authors:  Richard S Johnson; Michael T Davis; J Alex Taylor; Scott D Patterson
Journal:  Methods       Date:  2005-01-13       Impact factor: 3.608

Review 6.  Proteomic LC-MS systems using nanoscale liquid chromatography with tandem mass spectrometry.

Authors:  Yasushi Ishihama
Journal:  J Chromatogr A       Date:  2005-03-04       Impact factor: 4.759

Review 7.  Tandem mass spectrometry for peptide and protein sequence analysis.

Authors:  Joshua J Coon; John E P Syka; Jeffrey Shabanowitz; Donald F Hunt
Journal:  Biotechniques       Date:  2005-04       Impact factor: 1.993

8.  Intact-protein-based high-resolution three-dimensional quantitative analysis system for proteome profiling of biological fluids.

Authors:  Hong Wang; Shawn G Clouthier; Vladimir Galchev; David E Misek; Ulrich Duffner; Chang-Ki Min; Rong Zhao; John Tra; Gilbert S Omenn; James L M Ferrara; Samir M Hanash
Journal:  Mol Cell Proteomics       Date:  2005-02-09       Impact factor: 5.911

9.  Global analysis of protein expression in yeast.

Authors:  Sina Ghaemmaghami; Won-Ki Huh; Kiowa Bower; Russell W Howson; Archana Belle; Noah Dephoure; Erin K O'Shea; Jonathan S Weissman
Journal:  Nature       Date:  2003-10-16       Impact factor: 49.962

Review 10.  Computational methods for protein identification from mass spectrometry data.

Authors:  Leo McHugh; Jonathan W Arthur
Journal:  PLoS Comput Biol       Date:  2008-02       Impact factor: 4.475

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  4 in total

1.  Toward a Sample Metadata Standard in Public Proteomics Repositories.

Authors:  Yasset Perez-Riverol
Journal:  J Proteome Res       Date:  2020-09-22       Impact factor: 4.466

Review 2.  Engineered biological entities for drug delivery and gene therapy protein nanoparticles.

Authors:  Joan Domingo-Espín; Ugutz Unzueta; Paolo Saccardo; Escarlata Rodríguez-Carmona; José Luís Corchero; Esther Vázquez; Neus Ferrer-Miralles
Journal:  Prog Mol Biol Transl Sci       Date:  2011       Impact factor: 3.622

3.  Functional proteomics of barley and barley chloroplasts - strategies, methods and perspectives.

Authors:  Jørgen Petersen; Adelina Rogowska-Wrzesinska; Ole N Jensen
Journal:  Front Plant Sci       Date:  2013-03-18       Impact factor: 5.753

4.  Interactive Web Tool for Standardizing Proteomics Workflow for Liquid Chromatography-Mass Spectrometry Data.

Authors:  Sudhir Srivastava; Michael Merchant; Anil Rai; Shesh N Rai
Journal:  J Proteomics Bioinform       Date:  2019-05-23
  4 in total

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