International Journal of Human Genetics · 2017 · 10 citations · 6 references
ComputingBioinformaticsComputer ScienceComputational BiologyGene Expression AnalysisMachine LearningComputer-aided DiagnosisGene Expression ProfilingGene PredictionKernel MethodsOptimization For Machine LearningSupport Vector MachinesArtificial Intelligence For DetectionMachine Learning For DiagnosisMachine Learning-based DiagnosisMicroarray AnalysisSupport Vector ClassificationSupport Vector Machine ClassificationSupport Vector Regression
The main objective is to detect the disease-causing gene from microarray data and predict the results from the gene expression value. Many computer-assisted algorithms developed to predict the characteristic of a gene is done using machine learning and other bio-inspired algorithms. In this paper, seven works are proposed and compared to estimate the efficiency. The Support Vector Machine (SVM) optimized neuro-expert algorithm is developed to optimize these predictive results of both machine learning and bio-inspired algorithms and proven its effectiveness and efficiency in detecting the disease-causing gene than ever before.
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