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
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