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CBMS
2005
IEEE
14 years 2 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...
BIBE
2003
IEEE
121views Bioinformatics» more  BIBE 2003»
14 years 2 months ago
Time Series Analysis of Gene Expression and Location Data
We develop a method for integrating time series expression profiles and factor-gene binding data to quantify dynamic aspects of gene regulation. We estimate latencies for transcr...
Chen-Hsiang Yeang, Tommi Jaakkola
BMCBI
2007
134views more  BMCBI 2007»
13 years 9 months ago
Nearest Neighbor Networks: clustering expression data based on gene neighborhoods
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
BMCBI
2004
87views more  BMCBI 2004»
13 years 8 months ago
Selection of informative clusters from hierarchical cluster tree with gene classes
Background: A common clustering method in the analysis of gene expression data has been hierarchical clustering. Usually the analysis involves selection of clusters by cutting the...
Petri Törönen
BMCBI
2008
138views more  BMCBI 2008»
13 years 9 months ago
Methods for simultaneously identifying coherent local clusters with smooth global patterns in gene expression profiles
Background: The hierarchical clustering tree (HCT) with a dendrogram [1] and the singular value decomposition (SVD) with a dimension-reduced representative map [2] are popular met...
Yin-Jing Tien, Yun-Shien Lee, Han-Ming Wu, Chun-Ho...