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BMCBI
2008
160views more  BMCBI 2008»
13 years 9 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
2004
206views more  BMCBI 2004»
13 years 8 months ago
Combining gene expression data from different generations of oligonucleotide arrays
Background: One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public re...
Kyu Baek Hwang, Sek Won Kong, Steven A. Greenberg,...
BMCBI
2007
194views more  BMCBI 2007»
13 years 9 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
CIKM
2006
Springer
13 years 10 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
KIC
2000
13 years 10 months ago
Knowledge Discovery and Data Mining within a Design Environment
Designers, in the process of satisfying design requirements, generally encounter difficulties in, firstly, understanding the problem and secondly, finding a solution [Cross 1998]....
Mark K. D. Haffey, Alex H. B. Duffy