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BIOINFORMATICS
2004
51views more  BIOINFORMATICS 2004»
13 years 4 months ago
Approximate geodesic distances reveal biologically relevant structures in microarray data
Jens Nilsson, Thoas Fioretos, Mattias Höglund...
BMCBI
2006
203views more  BMCBI 2006»
13 years 4 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
KDD
2004
ACM
137views Data Mining» more  KDD 2004»
13 years 10 months ago
Mining scale-free networks using geodesic clustering
Many real-world graphs have been shown to be scale-free— vertex degrees follow power law distributions, vertices tend to cluster, and the average length of all shortest paths is...
Andrew Y. Wu, Michael Garland, Jiawei Han
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
13 years 5 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang
BMCBI
2004
181views more  BMCBI 2004»
13 years 4 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon