Minimum redundancy maximum relevance feature selection approach for temporal gene expression data-Reference-Cited by-同舟云学术

Minimum redundancy maximum relevance feature selection approach for temporal gene expression data

Published:2017-01-03 Issue:1 Volume:18 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Radovic Milos,Ghalwash Mohamed,Filipovic Nenad,Obradovic Zoran

Funder

Defense Advanced Research Projects Agency (DARPA) and the Army Research Office

Defense Advanced Research Projects Agency

Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/s12859-016-1423-9.pdf

Reference28 articles.

1. Yu L, Liu H. Feature selection for high-dimensional data: A fast correlation-based filter solution In: Fawcett T, Mishra N, editors. Proceedings of the 20th International Conference on Machine Learning (ICML-03). Menlo Park: The AAAI Press: 2003. p. 856–63.

2. Kohavi R, John GH. Relevance wrappers for feature subset selection. Artif. Intell. 1997; 97(1):273–324.

3. Lal TN, Chapelle O, Weston J, Elisseeff A. Embedded Methods In: Guyon I, Nikravesh M, Gunn S, Zadeh LA, editors. Feature Extraction: Foundations and Applications. Berlin: Springer: 2006. p. 137–65.

4. Saeys Y, Inza I, Larrañaga P. A review of feature selection techniques in bioinformatics. Bioinformatics. 2007; 23(19):2507–517.

5. Bolón-Canedo V, Sánchez-Maroño N, Alonso-Betanzos A, Benítez JM, Herrera F. A review of microarray datasets and applied feature selection methods. Information Sciences. 2014; 282:111–35.

Cited by 309 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sudden Cardiac Death Prediction by Fusing Electrocardiogram and Heart Rate Variability Signals;INT J ENG-IRAN;2025

2. Parametric study on global estimation models for compressive strength adopting various machine learning algorithms in concrete;Engineering Applications of Artificial Intelligence;2024-10

3. Discernment of textile fibers by polarization-sensitive Digital Holographic microscope and machine learning;Optics and Lasers in Engineering;2024-10

4. Radiomics Analysis of Intratumoral and Various Peritumoral Regions From Automated Breast Volume Scanning for Accurate Ki-67 Prediction in Breast Cancer Using Machine Learning;Academic Radiology;2024-09

5. A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis;Functional & Integrative Genomics;2024-08-19