Identification of dominant signaling pathways from proteomics expression data

The availability of the results of high-throughput analyses coming from ‘omic’ technologies has been one of the major driving forces of pathway biology. Analytical pathway biology strives to design a ‘pathway search engine’, where the input is the ‘omic’ data and the output is the list of activated...

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Bibliographic Details
Published in:Journal of proteomics 2008-04, Vol.71 (1), p.89-96
Main Authors: Zubarev, Roman A., Nielsen, Michael L., Fung, Eva M., Savitski, Mikhail M., Kel-Margoulis, Olga, Wingender, Edgar, Kel, Alexander
Format: Article
Language:English
Subjects:
Animals
Biologi
Biology
Cell and molecular biology
Cell Line, Tumor
Cell- och molekylärbiologi
Cells, Cultured
Computational Biology
Epidermal Growth Factor - metabolism
fas Receptor - metabolism
Gene Expression Profiling
Gene Expression Regulation
Genes
Humans
Medicin och hälsovetenskap
Mink
NATURAL SCIENCES
NATURVETENSKAP
Pathway analysis
Protein identification
Proteins
Proteome - metabolism
Proteomics
Reproducibility of Results
Signal Transduction
T-Lymphocytes - metabolism
Tandem mass spectrometry
Transforming Growth Factor beta - metabolism
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Summary:The availability of the results of high-throughput analyses coming from ‘omic’ technologies has been one of the major driving forces of pathway biology. Analytical pathway biology strives to design a ‘pathway search engine’, where the input is the ‘omic’ data and the output is the list of activated or dominant pathways in a given sample. Here we describe the first attempt to design and validate such a pathway search engine using as input expression proteomics data. The engine represents a specific workflow in computational tools developed originally for mRNA analysis ( BMC Bioinformatics 2006, 7 (Suppl 2), S13). Using our own datasets as well as data from recent proteomics literature we demonstrate that different dominant pathways (EGF, TGF β, stress, and Fas pathways) can be correctly identified even from limited datasets. Pathway search engines can find application in a variety of proteomics-related fields, from fundamental molecular biology to search for novel types of disease biomarkers.
ISSN:1874-3919
DOI:10.1016/j.jprot.2008.01.004