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KDD
2002
ACM
183views Data Mining» more  KDD 2002»
14 years 7 months ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
APBC
2003
13 years 8 months ago
Microarray Image Processing Based on Clustering and Morphological Analysis
Microarrays allow the monitoring of expressions for tens of thousands of genes simultaneously. Image analysis is an important aspect for microarray experiments that can affect sub...
Shuanhu Wu, Hong Yan
IDA
2007
Springer
13 years 6 months ago
An unsupervised clustering approach for leukaemia classification based on DNA micro-arrays data
: DNA micro-arrays provide thousands of genomic expressions on the same subject. A main issue is then to find the subset of genes whose degeneration is responsible of a certain typ...
Simone Garatti, Sergio Bittanti, Diego Liberati, A...
BIBE
2004
IEEE
107views Bioinformatics» more  BIBE 2004»
13 years 10 months ago
Enhanced pClustering and Its Applications to Gene Expression Data
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
Sungroh Yoon, Christine Nardini, Luca Benini, Giov...
BMCBI
2007
149views more  BMCBI 2007»
13 years 6 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin