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BMCBI
2006
134views more  BMCBI 2006»
13 years 7 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden
BMCBI
2006
92views more  BMCBI 2006»
13 years 7 months ago
Predicting survival outcomes using subsets of significant genes in prognostic marker studies with microarrays
Background: Genetic markers hold great promise for refining our ability to establish precise prognostic prediction for diseases. The development of comprehensive gene expression m...
Shigeyuki Matsui
WILF
2005
Springer
194views Fuzzy Logic» more  WILF 2005»
14 years 1 months ago
Learning Bayesian Classifiers from Gene-Expression MicroArray Data
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
Andrea Bosin, Nicoletta Dessì, Diego Libera...
CSB
2005
IEEE
205views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Fractal Clustering for Microarray Data Analysis
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
ICPR
2004
IEEE
14 years 8 months ago
Feature Selection and Gene Clustering from Gene Expression Data
In this article we describe an algorithm for feature selection and gene clustering from high dimensional gene expression data. The method is based on measuring similarity between ...
D. Dutta Majumder, Pabitra Mitra