New Variable Selection Method Using Interval Segmentation Purity with Application to Blockwise Kernel Transform Support Vector Machine Classification of High-Dimensional Microarray Data-Reference-Cited by-同舟云学术

New Variable Selection Method Using Interval Segmentation Purity with Application to Blockwise Kernel Transform Support Vector Machine Classification of High-Dimensional Microarray Data

Published:2009-07-31 Issue:8 Volume:49 Page:2002-2009
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Tang Li-Juan¹,Du Wen¹,Fu Hai-Yan¹,Jiang Jian-Hui¹,Wu Hai-Long¹,Shen Guo-Li¹,Yu Ru-Qin¹

Affiliation:

1. State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, P. R. China

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ci900032q

Reference26 articles.

1. Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring

2. Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data

3. Class Prediction by Nearest Shrunken Centroids, with Applications to DNA Microarrays

4. A CART-based approach to discover emerging patterns in microarray data

5. HLA-DQB1*0201

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