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» Evaluation of clustering algorithms for gene expression data
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BMCBI
2002
195views more  BMCBI 2002»
14 years 9 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
KDD
2003
ACM
152views Data Mining» more  KDD 2003»
15 years 10 months ago
Interactive exploration of coherent patterns in time-series gene expression data
Discovering coherent gene expression patterns in time-series gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we pr...
Daxin Jiang, Jian Pei, Aidong Zhang
APBC
2004
121views Bioinformatics» more  APBC 2004»
14 years 11 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
BMCBI
2007
156views more  BMCBI 2007»
14 years 9 months ago
Large-scale clustering of CAGE tag expression data
Background: Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. ...
Kazuro Shimokawa, Yuko Okamura-Oho, Takio Kurita, ...
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BIOCOMP
2006
14 years 11 months ago
A Heuristic Approach to Scoring Gene Clustering Algorithms
In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
Longde Yin, Chun-Hsi Huang