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» Clustering cancer gene expression data: a comparative study
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2009
ACM
15 years 4 months ago
Cloud technologies for bioinformatics applications
Executing large number of independent tasks or tasks that perform minimal inter-task communication in parallel is a common requirement in many domains. In this paper, we present o...
Xiaohong Qiu, Jaliya Ekanayake, Scott Beason, Thil...
BMCBI
2006
98views more  BMCBI 2006»
14 years 11 months ago
Quantitative comparison of EST libraries requires compensation for systematic biases in cDNA generation
Background: Publicly accessible EST libraries contain valuable information that can be utilized for studies of tissue-specific gene expression and processing of individual genes. ...
Donglin Liu, Joel H. Graber
BMCBI
2010
153views more  BMCBI 2010»
14 years 11 months ago
Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data
Background: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone ...
Benedikt Zacher, Pei Fen Kuan, Achim Tresch
90
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RSFDGRC
2005
Springer
192views Data Mining» more  RSFDGRC 2005»
15 years 5 months ago
An Open Source Microarray Data Analysis System with GUI: Quintet
We address Quintet, an R-based unified cDNA microarray data analysis system with GUI. Five principal categories of microarray data analysis have been coherently integrated in Quin...
Jun-kyoung Choe, Tae-Hoon Chung, Sunyong Park, Hwa...
92
Voted
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
15 years 6 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...