Feature selection method using WF-LASSO for gene expression data analysis

Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11 ◽

10.1145/2147805.2147889 ◽

2011 ◽

Author(s):

Ho Sun Shon ◽

Kyung-Sook Yang ◽

Che Woo Yoo ◽

Keun Ho Ryu

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Expression Data ◽

Gene Expression Data Analysis

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A Filter Feature Selection Method Based on MFA Score and Redundancy Excluding and It’s Application to Tumor Gene Expression Data Analysis

Interdisciplinary Sciences Computational Life Sciences ◽

10.1007/s12539-015-0272-y ◽

2015 ◽

Vol 7 (4) ◽

pp. 391-396 ◽

Author(s):

Jiangeng Li ◽

Lei Su ◽

Zenan Pang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Tumor Gene Expression ◽

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Feature Selection for Gene Expression Data Analysis – A Review

International Journal of Psychosocial Rehabilitation ◽

10.37200/ijpr/v24i5/pr2020695 ◽

2020 ◽

Vol 24 (5) ◽

pp. 6955-6964

Author(s):

Dr. Prema R

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

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A filter feature selection method based LLRFC and redundancy analysis for tumor classification using gene expression data

2016 12th World Congress on Intelligent Control and Automation (WCICA) ◽

10.1109/wcica.2016.7578590 ◽

2016 ◽

Author(s):

Jiangeng Li ◽

Xiaodan Li ◽

Wei Zhang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Redundancy Analysis ◽

Feature Selection Method ◽

Selection Method ◽

Tumor Classification ◽

Expression Data

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A Novel Feature Selection Method for Gene Expression Data Based on Samples Localization

Proceedings of the 2016 International Conference on Biological Engineering and Pharmacy (BEP 2016) ◽

10.2991/bep-16.2017.14 ◽

2017 ◽

Author(s):

Mingyue SHENG ◽

Wei DU ◽

Yuan TIAN ◽

Yanchun LIANG

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Expression Data

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Integrated Theory-and Data-Driven Feature Selection in Gene Expression Data Analysis

2017 IEEE 33rd International Conference on Data Engineering (ICDE) ◽

10.1109/icde.2017.223 ◽

2017 ◽

Author(s):

Vineet K. Raghu ◽

Xiaoyu Ge ◽

Panos K. Chrysanthis ◽

Panayiotis V. Benos

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Data Driven ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Integrated Theory

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Robust integrated framework for effective feature selection and sample classification and its application to gene expression data analysis

2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

10.1109/cibcb.2012.6217219 ◽

2012 ◽

Author(s):

Shang Gao ◽

Omar Addam ◽

Ala Qabaja ◽

Abdallah ElSheikh ◽

Omar Zarour ◽

...

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Expression Data ◽

Gene Expression Data Analysis ◽

Integrated Framework ◽

Sample Classification

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A Hybrid Feature Selection Method Using Gene Expression Data

2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering ◽

10.1109/bibe.2009.24 ◽

2009 ◽

Author(s):

Li-Yeh Chuang ◽

Kuo-Chuan Wu ◽

Cheng-Hong Yang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Expression Data

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A Review of Matched-pairs Feature Selection Methods for Gene Expression Data Analysis

Computational and Structural Biotechnology Journal ◽

10.1016/j.csbj.2018.02.005 ◽

2018 ◽

Vol 16 ◽

pp. 88-97 ◽

Author(s):

Sen Liang ◽

Anjun Ma ◽

Sen Yang ◽

Yan Wang ◽

Qin Ma

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Data Analysis ◽

Gene Expression Data ◽

Matched Pairs ◽

Expression Data ◽

Selection Methods ◽

Gene Expression Data Analysis

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Hybrid feature selection method using gene expression data

2008 IEEE Conference on Soft Computing in Industrial Applications ◽

10.1109/smcia.2008.5045960 ◽

2008 ◽

Author(s):

Li-Yeh Chuang ◽

Kuo-Chuan Wu ◽

Cheng-Hong Yang

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Expression Data

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sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic

Frontiers in Genetics ◽

10.3389/fgene.2020.00247 ◽

2020 ◽

Vol 11 ◽

Author(s):

Pijush Das ◽

Anirban Roychowdhury ◽

Subhadeep Das ◽

Susanta Roychoudhury ◽

Sucheta Tripathy

Keyword(s):

Gene Expression ◽

Support Vector Machine ◽

Feature Selection ◽

Gene Expression Data ◽

Feature Selection Method ◽

Selection Method ◽

Significant Feature ◽

Support Vector ◽

Expression Data

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