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IEEEMM
2007
146views more  IEEEMM 2007»
13 years 10 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
WABI
2004
Springer
132views Bioinformatics» more  WABI 2004»
14 years 3 months ago
Joint Analysis of DNA Copy Numbers and Gene Expression Levels
Abstract. Genomic instabilities, amplifications, deletions and translocations are often observed in tumor cells. In the process of cancer pathogenesis cells acquire multiple genom...
Doron Lipson, Amir Ben-Dor, Elinor Dehan, Zohar Ya...
WABI
2005
Springer
14 years 3 months ago
Time-Window Analysis of Developmental Gene Expression Data with Multiple Genetic Backgrounds
d Abstract] Tamir Tuller , Efrat Oron , Erez Makavy , Daniel A. Chamovitz † , and Benny Chor ‡ Tel-Aviv University, Tel-Aviv 69978, Israel. Abstract. We study gene expression d...
Tamir Tuller, Efrat Oron, Erez Makavy, Daniel A. C...
HIS
2008
13 years 11 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
André L. D. Rossi, André C. P. L. F....
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
14 years 3 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...