Literature DB >> 21063940

Analysis of phosphoproteomics data.

Christoph Schaab1.   

Abstract

Regulation of protein phosphorylation plays an important role in many cellular processes, particularly in signal transduction. Diseases such as cancer and inflammation are often linked to aberrant signaling pathways. Mass spectrometry-based methods allow monitoring the phosphorylation status in an unbiased and quantitative manner. The analysis of this data requires the application of advanced statistical methods, some of which can be borrowed from the gene expression analysis field. Nevertheless, these methods have to be enhanced or complemented by new methods. After reviewing the key concepts of phosphoproteomics and some major data analysis methods, these tools are applied to a real-world data set.

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Year:  2011        PMID: 21063940     DOI: 10.1007/978-1-60761-987-1_3

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


  7 in total

1.  Phosphosignature predicts dasatinib response in non-small cell lung cancer.

Authors:  Martin Klammer; Marc Kaminski; Alexandra Zedler; Felix Oppermann; Stephanie Blencke; Sandra Marx; Stefan Müller; Andreas Tebbe; Klaus Godl; Christoph Schaab
Journal:  Mol Cell Proteomics       Date:  2012-05-21       Impact factor: 5.911

2.  Analysis of high accuracy, quantitative proteomics data in the MaxQB database.

Authors:  Christoph Schaab; Tamar Geiger; Gabriele Stoehr; Juergen Cox; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2012-02-02       Impact factor: 5.911

3.  Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

Authors:  Martin Klammer; J Nikolaj Dybowski; Daniel Hoffmann; Christoph Schaab
Journal:  PLoS One       Date:  2015-06-17       Impact factor: 3.240

4.  Identification of significant features by the Global Mean Rank test.

Authors:  Martin Klammer; J Nikolaj Dybowski; Daniel Hoffmann; Christoph Schaab
Journal:  PLoS One       Date:  2014-08-13       Impact factor: 3.240

Review 5.  Bacterial phosphoproteomic analysis reveals the correlation between protein phosphorylation and bacterial pathogenicity.

Authors:  Ruiguang Ge; Weiran Shan
Journal:  Genomics Proteomics Bioinformatics       Date:  2011-10       Impact factor: 7.691

6.  Phosphoproteome Analysis Reveals Differential Mode of Action of Sorafenib in Wildtype and Mutated FLT3 Acute Myeloid Leukemia (AML) Cells.

Authors:  Catrin Roolf; Nikolaj Dybowski; Anett Sekora; Stefan Mueller; Gudrun Knuebel; Andreas Tebbe; Hugo Murua Escobar; Klaus Godl; Christian Junghanss; Christoph Schaab
Journal:  Mol Cell Proteomics       Date:  2017-04-27       Impact factor: 5.911

Review 7.  Phosphoproteomics and lung cancer research.

Authors:  Elena López; William C S Cho
Journal:  Int J Mol Sci       Date:  2012-09-26       Impact factor: 5.923

  7 in total

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