Literature DB >> 19306877

Bioinformatics analysis of mass spectrometry-based proteomics data sets.

Chanchal Kumar1, Matthias Mann.   

Abstract

Proteomics has made tremendous progress, attaining throughput and comprehensiveness so far only seen in genomics technologies. The consequent avalanche of proteome level data poses great analytical challenges for downstream interpretation. We review bioinformatic analysis of qualitative and quantitative proteomic data, focusing on current and emerging paradigms employed for functional analysis, data mining and knowledge discovery from high resolution quantitative mass spectrometric data. Many bioinformatics tools developed for microarrays can be reused in proteomics, however, the uniquely quantitative nature of proteomics data also offers entirely novel analysis possibilities, which directly suggest and illuminate biological mechanisms.

Mesh:

Year:  2009        PMID: 19306877     DOI: 10.1016/j.febslet.2009.03.035

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  37 in total

Review 1.  Decoding signalling networks by mass spectrometry-based proteomics.

Authors:  Chunaram Choudhary; Matthias Mann
Journal:  Nat Rev Mol Cell Biol       Date:  2010-05-12       Impact factor: 94.444

Review 2.  Phosphoproteomic analysis: an emerging role in deciphering cellular signaling in human embryonic stem cells and their differentiated derivatives.

Authors:  Brian T D Tobe; Junjie Hou; Andrew M Crain; Ilyas Singec; Evan Y Snyder; Laurence M Brill
Journal:  Stem Cell Rev Rep       Date:  2012-03       Impact factor: 5.739

Review 3.  Guidelines for the design, analysis and interpretation of 'omics' data: focus on human endometrium.

Authors:  Signe Altmäe; Francisco J Esteban; Anneli Stavreus-Evers; Carlos Simón; Linda Giudice; Bruce A Lessey; Jose A Horcajadas; Nick S Macklon; Thomas D'Hooghe; Cristina Campoy; Bart C Fauser; Lois A Salamonsen; Andres Salumets
Journal:  Hum Reprod Update       Date:  2013-09-29       Impact factor: 15.610

4.  Comparative analysis to guide quality improvements in proteomics.

Authors:  Matthias Mann
Journal:  Nat Methods       Date:  2009-10       Impact factor: 28.547

5.  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

6.  GProX, a user-friendly platform for bioinformatics analysis and visualization of quantitative proteomics data.

Authors:  Kristoffer T G Rigbolt; Jens T Vanselow; Blagoy Blagoev
Journal:  Mol Cell Proteomics       Date:  2011-05-20       Impact factor: 5.911

7.  A quantitative proteomics analysis of subcellular proteome localization and changes induced by DNA damage.

Authors:  François-Michel Boisvert; Yun Wah Lam; Douglas Lamont; Angus I Lamond
Journal:  Mol Cell Proteomics       Date:  2009-12-21       Impact factor: 5.911

Review 8.  Tools for label-free peptide quantification.

Authors:  Sven Nahnsen; Chris Bielow; Knut Reinert; Oliver Kohlbacher
Journal:  Mol Cell Proteomics       Date:  2012-12-17       Impact factor: 5.911

9.  A quantitative investigation of fucosylated serum glycoproteins with application to esophageal adenocarcinoma.

Authors:  Benjamin Mann; Milan Madera; Iveta Klouckova; Yehia Mechref; Lacey E Dobrolecki; Robert J Hickey; Zane T Hammoud; Milos V Novotny
Journal:  Electrophoresis       Date:  2010-06       Impact factor: 3.535

10.  Reconstruction of metabolic pathways, protein expression, and homeostasis machineries across maize bundle sheath and mesophyll chloroplasts: large-scale quantitative proteomics using the first maize genome assembly.

Authors:  Giulia Friso; Wojciech Majeran; Mingshu Huang; Qi Sun; Klaas J van Wijk
Journal:  Plant Physiol       Date:  2010-01-20       Impact factor: 8.340

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