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» Algorithms for Finding Gene Clusters
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168
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CSB
2004
IEEE
135views Bioinformatics» more  CSB 2004»
15 years 7 months ago
Selection of Patient Samples and Genes for Outcome Prediction
Gene expression profiles with clinical outcome data enable monitoring of disease progression and prediction of patient survival at the molecular level. We present a new computatio...
Huiqing Liu, Jinyan Li, Limsoon Wong
266
Voted
FUIN
2011
358views Cryptology» more  FUIN 2011»
14 years 7 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
115
Voted
COCOA
2008
Springer
15 years 5 months ago
On Recovering Syntenic Blocks from Comparative Maps
A genomic map is represented by a sequence of gene markers, and a gene marker can appear in several different genomic maps, in either positive or negative form. A strip (syntenic b...
Zhixiang Chen, Bin Fu, Minghui Jiang, Binhai Zhu
125
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DATAMINE
2006
157views more  DATAMINE 2006»
15 years 3 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
157
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GECCO
2007
Springer
197views Optimization» more  GECCO 2007»
15 years 9 months ago
Computational intelligence techniques: a study of scleroderma skin disease
This paper presents an analysis of microarray gene expression data from patients with and without scleroderma skin disease using computational intelligence and visual data mining ...
Julio J. Valdés, Alan J. Barton