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  1. 1
    A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data

    A Study On Gene Selection And Classification Algorithms For Classification Of Microarray Gene Expression Data by Yeo, Lee Chin, Deris, Safaai

    Published 2005
    “…In This Paper, A Study On Numerous Combinations Of Gene Selection Techniques And Classification Algorithms For Classification Of Microarray Gene Expression Data Is Presented. …”
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  2. 2
    A combinatory algorithm of univariate and multivariate gene selection

    A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2009
    “…Gene selection is usually based on univariate or multivariate methods. …”
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  3. 3
    Gene selection for high dimensional data using k-means clustering algorithm and statistical approach

    Gene selection for high dimensional data using k-means clustering algorithm and statistical approach by Ahmad, Farzana Kabir, Yusof, Yuhanis, Othman, Nor Hayati

    Published 2014
    “…Thus, selection of relevant genes is a challenging issue in microarray data analysis and has been a central research focus.This study proposed kmeans clustering algorithm to groups the relevant genes. …”
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    Conference or Workshop Item
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  4. 4
    Effective gene selection techniques for classification of gene expression data

    Effective gene selection techniques for classification of gene expression data by Yeo, Lee Chin

    Published 2005
    “…When classifying tissue samples, gene selection plays an important role. In this research, some existing gene selection techniques are studied and better gene selection techniques are proposed and developed. …”
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  5. 5
    Gene subset selection for lung cancer classification using a multi-objective strategy

    Gene subset selection for lung cancer classification using a multi-objective strategy by Mohamad, Mohd. Saberi, Omatu, Sigeru, Deris, Safaai, Yoshioka, Michifuci

    Published 2008
    “…It has been shown that selecting a small subset of genes can lead to improved classification accuracy. …”
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  6. 6
    Gene Selection For Cancer Classification Based On Xgboost Classifier

    Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

    Published 2022
    “…Gene selection is the technique that applied to the gene selection dataset, such as DNA microarray, which is develop to reduce the less informative gene, so that the selected gene is related to the disease diagnosis. …”
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  7. 7
    New entropy-based method for gene selection

    New entropy-based method for gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2009
    “…In this paper, we use Shannon theorem and penalized logistic regression (PLR) as a probability estimator to present a new algorithm for dimension reduction and collect a subset of representative genes of gene expression profile. …”
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  8. 8
    Using fuzzy association rule mining in cancer classification

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. …”
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  9. 9
    A model for gene selection and classification of gene expression data

    A model for gene selection and classification of gene expression data by Mohamad, Mohd Saberi, Omatu, Sigeru, Deris, Safaai, Mohd Hashim, Siti Zaiton

    Published 2007
    “…A model for gene selection and classification has been developed by using a filter approach, and an improved hybrid of the genetic algorithm and a support vector machine classifier. …”
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  10. 10
    Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification

    Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification by Mohamad, Mohd. Saberi, Deris, Safaai, Hashim, Siti Zaiton Mohd.

    Published 2007
    “…We introduce an improved version of hybrid of genetic algorithm and support vector machine for genes selection and classification. …”
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  11. 11
    Machine learning-based leukemia classification using gene expression for accurate diagnosis

    Machine learning-based leukemia classification using gene expression for accurate diagnosis by Mahmoud, Amena, Talpur, Kazim Raza, Saini, Shilpa, Talpur, Bandeh Ali, Shah, Asadullah, Zaki, John

    Published 2025
    “…A dataset has been taken and thus preprocessed which consist of profiles of gene expression of patients having leukemia. Then the feature selection techniques have been used for classification of informative genes. …”
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    Proceeding Paper
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  12. 12
    An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes

    An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes by Mohd Saberi, Mohamad, Sigeru, Omatu, Safaai, Deris, Yoshioka, Michifumi, Afnizanfaizal, Abdullah, Zuwairie, Ibrahim

    Published 2013
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  13. 13
    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach

    Reference gene validation for gene expression normalization in canine osteosarcoma: a geNorm algorithm approach by Selvarajah, Gayathri Thevi, Bonestroo, Floor A. S., Timmermans Sprang, Elpetra P. M., Kirpensteijn, Jolle, Mol, Jan A.

    Published 2017
    “…This study aimed to validate a panel of reference genes commonly used for normalization of canine OS gene expression data using the geNorm algorithm. qPCR analysis of nine canine reference genes was performed on 40 snap-frozen primary OS tumors and seven cell lines. …”
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  14. 14
    Filter-Wrapper Methods For Gene Selection In Cancer Classification

    Filter-Wrapper Methods For Gene Selection In Cancer Classification by Alomari, Osama Ahmad Suleiman

    Published 2018
    “…This study proposes new hybrid filter-wrapper methods based on Maximum Relevancy Minimum Redundancy (MRMR) as a filter approach and adapted bat-inspired algorithm (BA) as a wrapper approach. First, MRMR hybridisation and BA adaptation are investigated to resolve the gene selection problem. …”
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  15. 15
    Integrated framework with association analysis for gene selection in microarray data classification

    Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

    Published 2011
    “…To achieve that, an integrated framework with a new gene selection method was developed to improve classification performance in terms of accuracy and number of selected genes. …”
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  16. 16
    Gene Selection for Cancer Classification Based on XGBoost

    Gene Selection for Cancer Classification Based on XGBoost by Chuan, Teo Voon, Tomal, Md Raihanul Islam, Moorthy, Kohbalan, Howe, Chan Weng

    Published 2025
    “…This research focuses on improving gene selection for cancer classification using the XGBoost classifier, an efficient open-source implementation of the gradient boosted trees algorithm. …”
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  17. 17
    Application Of Genetic Algorithms For Robust Parameter Optimization

    Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

    Published 2010
    “…This reproduction is established in terms of selection, crossover and mutation of reproducing genes. …”
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  18. 18
    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. …”
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  19. 19
    Selection of reference genes for quantitative real-time PCR normalization in Ganoderma-infected oil palm (Elaies guineensis) seedlings

    Selection of reference genes for quantitative real-time PCR normalization in Ganoderma-infected oil palm (Elaies guineensis) seedlings by Kwan, Yee Min, Meon, Sariah, Ho, Chai Ling, Wong, Mui Yun

    Published 2016
    “…NormFinder and BestKeeper algorithms were used to cross-validate the expression stability of the candidate reference genes. …”
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  20. 20
    Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification

    Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification by Nasrudin, Nurul Athirah, Chan, Weng Howe, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi, Kasim, Shahreen

    Published 2017
    “…Secondly, Support Vector Machine with Least Absolute Shrinkage and Selection Operator algorithm (SVM-LASSO) is proposed, which to find informative genes for each pathway to ensure efficient gene selection and classification in every pathway. …”
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