By Topic

Analysis of incomplete gene expression dataset through protein-protein interaction information

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Raimon Massanet-Vila ; Department of ESAII. Technical University of Catalonia (UPC). Address: Pau Gargallo 5, 08028 Barcelona. Spain ; Teresa Padro ; Anna Cardus ; Lina Badimon
more authors

This paper shows a graph based method to analyze proteomic expression data. The method allows the prediction of the expression of genes not measured by the gene expression technology based on the local connectivity properties of the measured differentially expressed gene set. The prediction of the expression jointly with the stability of this prediction as a function of the variation of the initial expressed set is computed. The method is able to correctly predict one third of the proteins with independence of variations on the selection of the initial set. The algorithm is validated through a Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometer (MALDI-TOF) protein expression experiment aiming the study of the protein expression patterns and post-translational modifications in human endothelial vascular cells exposed to atherosclerotic levels of Low Density Lipoproteins (LDL).

Published in:

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Date of Conference:

Aug. 30 2011-Sept. 3 2011