Search Results - (( gene selection based algorithm ) OR ( java application using algorithm ))
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Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…This leads to the classification accuracy and genes subset size problem. Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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A combinatory algorithm of univariate and multivariate gene selection
Published 2009“…Gene selection is usually based on univariate or multivariate methods. …”
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New entropy-based method for gene selection
Published 2009“…Breast cancer, leukemia, colon and lung datasets have been classified based on proposed gene selection algorithm by PLR classifier. …”
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Gene Selection For Cancer Classification Based On Xgboost Classifier
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Undergraduates Project Papers -
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Effective gene selection techniques for classification of gene expression data
Published 2005“…Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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6
RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Using fuzzy association rule mining in cancer classification
Published 2011“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…However, most of the existing gene selection methods are statistical analyses and purely based on gene expression values in the identification of differentially expressed genes. …”
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10
Provider independent cryptographic tools
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Monograph -
11
Machine learning-based leukemia classification using gene expression for accurate diagnosis
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Proceeding Paper -
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
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. The user participates in the search by proposing a new individual. …”
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13
Mutable Composite Firefly Algorithm for Microarray-Based Cancer Classification
Published 2024“…Thus, a swarm-based hybrid approach is proposed for cancer classification with a new variant of the Firefly Algorithm (FA) and Correlation-based Feature Selection (CFS) filter. …”
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Pathway-based analysis with Support Vector Machine (SVM-LASSO) for gene selection and classification
Published 2017“…Moreover, biological validation has been done on the selected genes based on biological literature and biological databases. …”
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Selecting informative genes from leukemia gene expression data using a hybrid approach for cancer classification
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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Book Section -
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Filter-Wrapper Methods For Gene Selection In Cancer Classification
Published 2018“…First, MRMR hybridisation and BA adaptation are investigated to resolve the gene selection problem. The proposed method is called MRMR-BA.…”
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17
The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Monograph -
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Gene Selection for Cancer Classification Based on XGBoost
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Pathway-based analysis with support vector machine (SVM-LASSO) for gene selection and classification
Published 2017“…Moreover, biological validation have been done on the selected genes based on biological literatures and biological databases. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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