Title :
Discrete Time Evolution of Proteomic Biomarkers
Author :
Gnabasik, David ; Alaghband, Gita
Author_Institution :
Coll. of Eng. & Appl. Sci., Univ. of Colorado Denver, Denver, CO, USA
Abstract :
We measured a panel of 12 cytokines in seven different populations: i.e., healthy non-smokers, healthy smokers, COPD, Aden carcinoma and Squamous cell carcinoma of the lung. From these 12 biomarkers of host response to lung disease we have developed a computational and visual model that reliably distinguishes these clinical types. Protein biomarker behavior models are developed as the topological evolution of linear discrete systems from changes in patient protein sample concentrations.
Keywords :
cellular biophysics; diseases; lung; proteins; proteomics; topology; COPD; adenocarcinoma cell carcinoma; computational model; cytokines; discrete time evolution; healthy nonsmokers; healthy smokers; host response; linear discrete systems; lung disease; patient protein sample concentrations; protein biomarker behavior models; squamous cell carcinoma; topological evolution; visual model; Biological system modeling; Computational modeling; Equations; Mathematical model; Proteins; Proteomics; cytokine biomarker; discrete time evolution; proteomics; topological analysis;
Conference_Titel :
Computational Science and Computational Intelligence (CSCI), 2014 International Conference on
Conference_Location :
Las Vegas, NV
DOI :
10.1109/CSCI.2014.87
