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BMCBI
2008
160views more  BMCBI 2008»
13 years 6 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
BMCBI
2010
160views more  BMCBI 2010»
13 years 6 months ago
Extracting consistent knowledge from highly inconsistent cancer gene data sources
Background: Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diver...
Xue Gong, Ruihong Wu, Yuannv Zhang, Wenyuan Zhao, ...
BMCBI
2007
207views more  BMCBI 2007»
13 years 6 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
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ESANN
2006
13 years 7 months ago
Selection of more than one gene at a time for cancer prediction from gene expression data
A new gene selection method capable of selecting more than one gene at a time is introduced. This characteristic contrasts it with almost all known methods assuming that there are ...
Oleg Okun, Nikolay G. Zagoruiko, Alexessander Alve...
BMCBI
2010
125views more  BMCBI 2010»
13 years 6 months ago
Asymmetric microarray data produces gene lists highly predictive of research literature on multiple cancer types
Background: Much of the public access cancer microarray data is asymmetric, belonging to datasets containing no samples from normal tissue. Asymmetric data cannot be used in stand...
Noor B. Dawany, Aydin Tozeren