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» E-CAST: A Data Mining Algorithm for Gene Expression Data
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ADMA
2009
Springer
212views Data Mining» more  ADMA 2009»
14 years 2 months ago
Automating Gene Expression Annotation for Mouse Embryo
It is of high biomedical interest to identify gene interactions and networks that are associated with developmental and physiological functions in the mouse embryo. There are now v...
Liangxiu Han, Jano I. van Hemert, Richard A. Baldo...
BMEI
2009
IEEE
13 years 9 months ago
An Improved Probabilistic Model for Finding Differential Gene Expression
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
Li Zhang, Xuejun Liu
NIPS
2003
13 years 9 months ago
Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms
New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...
Claudio Gentile
PSB
2004
13 years 9 months ago
Motif Discovery in Heterogeneous Sequence Data
This paper introduces the first integrated algorithm designed to discover novel motifs in heterogeneous sequence data, which is comprised of coregulated genes from a single genome...
Amol Prakash, Mathieu Blanchette, Saurabh Sinha, M...
ICDE
2004
IEEE
133views Database» more  ICDE 2004»
14 years 9 months ago
GenExplore: Interactive Exploration of Gene Interactions from Microarray Data
DNA Microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liyin...