A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization

Genomics ◽

10.1016/j.ygeno.2016.05.001 ◽

2016 ◽

Vol 107 (6) ◽

pp. 231-238 ◽

Author(s):

Fatemeh Vafaee Sharbaf ◽

Sara Mosafer ◽

Mohammad Hossein Moattar

Keyword(s):

Ant Colony Optimization ◽

Microarray Data ◽

Gene Selection ◽

Learning Automata ◽

Data Classification ◽

Hybrid Gene ◽

Selection Approach ◽

Cellular Learning Automata

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Gene selection for microarray data classification using a novel ant colony optimization

Neurocomputing ◽

10.1016/j.neucom.2015.05.022 ◽

2015 ◽

Vol 168 ◽

pp. 1024-1036 ◽

Author(s):

Sina Tabakhi ◽

Ali Najafi ◽

Reza Ranjbar ◽

Parham Moradi

Keyword(s):

Ant Colony Optimization ◽

Microarray Data ◽

Gene Selection ◽

Data Classification ◽

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GT-kernelPLS: Game theory based hybrid gene selection method for microarray data classification

2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) ◽

10.1109/snpd.2015.7176202 ◽

2015 ◽

Author(s):

Adnan Shakoor ◽

Qinke Peng ◽

Shiquan Sun ◽

Xiao Wang ◽

Jia Lv

Keyword(s):

Game Theory ◽

Microarray Data ◽

Gene Selection ◽

Data Classification ◽

Selection Method ◽

Gene Selection Method ◽

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Cancer Detection Based on Microarray Data Classification with Ant Colony Optimization and Modified Backpropagation Conjugate Gradient Polak-Ribiére

2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA) ◽

10.1109/ic3ina.2018.8629506 ◽

2018 ◽

Author(s):

D. P. Aldryan ◽

Adiwijaya ◽

Aditsania Annisa

Keyword(s):

Ant Colony Optimization ◽

Cancer Detection ◽

Microarray Data ◽

Conjugate Gradient ◽

Data Classification ◽

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A novel filter-wrapper hybrid gene selection approach for microarray data based on multi-objective forest optimization algorithm

Decision Science Letters ◽

10.5267/j.dsl.2020.5.006 ◽

2020 ◽

pp. 271-290

Author(s):

Babak Nouri-Moghaddam ◽

Mehdi Ghazanfari ◽

Mohammad Fathian

Keyword(s):

Microarray Data ◽

Optimization Algorithm ◽

Gene Selection ◽

Hybrid Gene ◽

Multi Objective ◽

Selection Approach

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A Hybrid Gene Selection Method Based on ReliefF and Ant Colony Optimization Algorithm for Tumor Classification

Scientific Reports ◽

10.1038/s41598-019-45223-x ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

Lin Sun ◽

Xianglin Kong ◽

Jiucheng Xu ◽

Zhan’ao Xue ◽

Ruibing Zhai ◽

...

Keyword(s):

Ant Colony Optimization ◽

Optimization Algorithm ◽

Gene Selection ◽

Selection Method ◽

Tumor Classification ◽

Ant Colony Optimization Algorithm ◽

Gene Selection Method ◽

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Improving Microarray Data Classification Using Optimized Clustering-Based Hybrid Gene Selection Algorithm

Journal of Advanced Research in Dynamical and Control Systems ◽

10.5373/jardcs/v12sp3/20201283 ◽

2020 ◽

Vol 51 (SP3) ◽

pp. 486-495

Author(s):

Saravanakumar D.

Keyword(s):

Microarray Data ◽

Gene Selection ◽

Data Classification ◽

Selection Algorithm ◽

Hybrid Gene ◽

Gene Selection Algorithm

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Random forest for gene selection and microarray data classification

Bioinformation ◽

10.6026/97320630007142 ◽

2011 ◽

Vol 7 (3) ◽

pp. 142-146 ◽

Author(s):

Kohbalan Moorthy ◽

Mohd Saberi Mohamad

Keyword(s):

Random Forest ◽

Microarray Data ◽

Gene Selection ◽

Data Classification

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A GALA Based Hybrid Gene Selection Model for Identification of Relevant Genes for Cancer Microarray Data

Smart Innovation, Systems and Technologies - Intelligent and Cloud Computing ◽

10.1007/978-981-15-5971-6_89 ◽

2020 ◽

pp. 827-835

Author(s):

Barnali Sahu ◽

Alok Kumar Jagadev

Keyword(s):

Microarray Data ◽

Gene Selection ◽

Selection Model ◽

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A Novel Hybrid Gene Selection Approach Based on ReliefF and FCBF

International Journal of Digital Content Technology and its Applications ◽

10.4156/jdcta.vol5.issue10.48 ◽

2011 ◽

Vol 5 (10) ◽

pp. 404-411 ◽

Author(s):

JianJiao Chen ◽

Anping Song ◽

Wu Zhang

Keyword(s):

Gene Selection ◽

Hybrid Gene ◽

Selection Approach

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A Hybrid Improved Ant Colony Optimization and Random Forests Feature Selection Method for Microarray Data

2009 Fifth International Joint Conference on INC, IMS and IDC ◽

10.1109/ncm.2009.66 ◽

2009 ◽

Author(s):

Wen Xiong ◽

Cong Wang

Keyword(s):

Feature Selection ◽

Ant Colony Optimization ◽

Random Forests ◽

Microarray Data ◽

Feature Selection Method ◽

Selection Method ◽

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