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CIKM
2004
Springer
13 years 10 months ago
Mining gene expression datasets using density-based clustering
Given the recent advancement of microarray technologies, we present a density-based clustering approach for the purpose of co-expressed gene cluster identification. The underlyin...
Seokkyung Chung, Jongeun Jun, Dennis McLeod
BIBE
2007
IEEE
176views Bioinformatics» more  BIBE 2007»
13 years 11 months ago
HICCUP: Hierarchical Clustering Based Value Imputation using Heterogeneous Gene Expression Microarray Datasets
Abstract—A novel microarray value imputation method, HICCUP1 , is presented. HICCUP improves upon existing value imputation methods in the several ways. (1) By judiciously integr...
Qiankun Zhao, Prasenjit Mitra, Dongwon Lee, Jaewoo...
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 5 months ago
A highly-usable projected clustering algorithm for gene expression profiles
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...
Kevin Y. Yip, David W. Cheung, Michael K. Ng
AUSDM
2006
Springer
107views Data Mining» more  AUSDM 2006»
13 years 8 months ago
Using a Kernel-Based Approach to Visualize Integrated Chronic Fatigue Syndrome Datasets
We describe the use of a kernel
Ahmad Al-Oqaily, Paul J. Kennedy
BMCBI
2006
183views more  BMCBI 2006»
13 years 4 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...