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» Clustering Genes Using Heterogeneous Data Sources
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BMCBI
2008
104views more  BMCBI 2008»
13 years 11 months ago
Missing value imputation improves clustering and interpretation of gene expression microarray data
Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value i...
Johannes Tuikkala, Laura Elo, Olli Nevalainen, Ter...
ISBI
2006
IEEE
14 years 11 months ago
Clustering gene expression patterns of fly embryos
The spatio-temporal patterning of gene expression in early embryos is an important source of information for understanding the functions of genes involved in development. Most ana...
Hanchuan Peng, Fuhui Long, Michael B. Eisen, Eugen...
JCB
2002
160views more  JCB 2002»
13 years 10 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...
IADIS
2008
14 years 13 days ago
Design of an Automated System for Clustering Heterogeneous Data
The goal of this work is to study the feasibility of a Heterogeneous Data Classification and Search (HDCS) system and to provide a possible design for its implementing. In order t...
Dorin Carstoiu, Alexandra Cernian, Adriana Olteanu...
COMAD
2008
14 years 14 days ago
Information Integration Across Heterogeneous Sources: Where Do We Stand and How to Proceed?
Today, information integration has assumed a completely different, complex connotation than what it used to be. The advent of the Internet, the proliferation of information source...
Aditya Telang, Sharma Chakravarthy, Yan Huang