DocumentCode :
2767634
Title :
Integration of statistical models and visualization tools to characterize microRNA networks influencing cancer
Author :
Karnia, James ; Delfino, Kristin R. ; Villamil, Maria B. ; Caetano-Anolles, Gustavo ; Rodriguez-Zas, Sandra L.
Author_Institution :
Dept. of Animal Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fYear :
2011
fDate :
12-15 Nov. 2011
Firstpage :
1009
Lastpage :
1011
Abstract :
Gene expression microarray experiments can be used to infer the topology of co-expression networks between genes in the immune-system pathways. Immune-system pathways are highly dimensional, including numerous gene nodes and edges connecting nodes. A bioinformatics strategy to infer and confirm gene co-expression networks was developed and applied to two major immune-system pathways. In total, 182 and 356 co-expression profiles between pairs of genes were identified in the NOD-like and B-cell receptor signaling pathways. The distinct distribution of the sign of the relationships among the pathways offered additional insights into the network.
Keywords :
DNA; bioinformatics; cancer; cellular biophysics; genetics; medical diagnostic computing; molecular biophysics; statistical analysis; B-cell receptor signaling pathway; NOD-like receptor signaling pathway; bioinformatics; cancer; edge connecting nodes; gene expression microarray; gene nodes; immune-system pathways; microRNA networks; statistical models; visualization tools; Bioinformatics; Correlation; Gene expression; Immune system; Mice; Probes; Solids; B-cell receptor; Cytokine; NOD-like receptor; chemokine; microarray;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2011 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4577-1612-6
Type :
conf
DOI :
10.1109/BIBMW.2011.6112541
Filename :
6112541
Link To Document :
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