A Hybrid SOM-SVM Approach for the Zebrafish Gene Expression Analysis
暂无分享,去创建一个
Rudy Setiono | Xin Liu | Wei Wu | Min Xu | Jin-Rong Peng
[1] Weiping Ma,et al. Embryogenesis Microarray for Profiling Gene Expression Patterns during 15,000 Unique Zebrafish Est Clusters and Their Future Use in Material Supplemental , 2022 .
[2] Nello Cristianini,et al. Support vector machine classification and validation of cancer tissue samples using microarray expression data , 2000, Bioinform..
[3] Jarkko Venna,et al. Analysis and visualization of gene expression data using Self-Organizing Maps , 2002, Neural Networks.
[4] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[5] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[6] Teuvo Kohonen,et al. The self-organizing map , 1990, Neurocomputing.
[7] J. Mesirov,et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.
[8] D Haussler,et al. Knowledge-based analysis of microarray gene expression data by using support vector machines. , 2000, Proceedings of the National Academy of Sciences of the United States of America.
[9] Stan Matwin,et al. Learning When Negative Examples Abound , 1997, ECML.
[10] Susmita Datta,et al. Comparisons and validation of statistical clustering techniques for microarray gene expression data , 2003, Bioinform..