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BMCBI
2007
134views more  BMCBI 2007»
13 years 5 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
2011
12 years 8 months ago
Clustering gene expression data with a penalized graph-based metric
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
Ariel E. Bayá, Pablo M. Granitto
BMCBI
2010
120views more  BMCBI 2010»
13 years 5 months ago
Examination of the relationship between essential genes in PPI network and hub proteins in reverse nearest neighbor topology
Background: In many protein-protein interaction (PPI) networks, densely connected hub proteins are more likely to be essential proteins. This is referred to as the "centralit...
Kang Ning, Hoong Kee Ng, Sriganesh Srihari, Hon Wa...
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 8 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
IJCNN
2008
IEEE
13 years 11 months ago
Dataset complexity can help to generate accurate ensembles of k-nearest neighbors
— Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small ...
Oleg Okun, Giorgio Valentini