DocumentCode :
1605034
Title :
Finding Co-Clusters of Genes and Clinical Parameters
Author :
Yoon, Sungroh ; Benini, Luca ; De Micheli, Giovanni
Author_Institution :
Comput. Syst. Lab., Stanford Univ., CA
fYear :
2006
Firstpage :
906
Lastpage :
912
Abstract :
For better understanding of genetic mechanisms underlying clinical observations, we often want to determine which genes and clinical traits are interrelated. We introduce a computational method that can find co-clusters or groups of genes and clinical parameters that are believed to be closely related to each other based upon given empirical information. The proposed method was tested with data from an acute myelogenous leukemia (AML) study and identified statistically significant co-clusters of genes and clinical traits. The validation of our results with gene ontology (GO) as well as the literature suggest that the proposed method can provide biologically meaningful co-clusters of genes and traits
Keywords :
blood; cancer; cellular biophysics; genetics; medical computing; molecular biophysics; ontologies (artificial intelligence); acute myelogenous leukemia; clinical parameters; gene co-clusters; gene ontology; genetic mechanisms; DNA; Gene expression; Genetics; Large-scale systems; Monitoring; Ontologies; Testing; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
Type :
conf
DOI :
10.1109/IEMBS.2005.1616562
Filename :
1616562
Link To Document :
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