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Putative drug targets in Rhizopus oryzae: in-silico insight., , , , , , and . Int. J. Bioinform. Res. Appl., 9 (6): 595-603 (2013)Improving Prediction Accuracy of Microarray Cancer Data with Non-negative Matrix Factorization and Its Variant., , and . BIBM, page 2227-2234. IEEE, (2020)Variance Based Particle Swarm Optimization for Function Optimization and Feature Selection., , , and . SEMCCO, volume 9873 of Lecture Notes in Computer Science, page 104-115. Springer, (2015)Using Deep Learning to Classify X-ray Images of Potential Tuberculosis Patients., , and . BIBM, page 2368-2375. IEEE Computer Society, (2018)Improved microarray data analysis using feature selection methods with machine learning methods., , and . BIBM, page 1527-1534. IEEE Computer Society, (2016)Markov blanket: Efficient strategy for feature subset selection method for high dimensional microarray cancer datasets., , and . BIBM, page 1864-1871. IEEE Computer Society, (2017)SVM Classifier Based Feature Selection Using GA, ACO and PSO for siRNA Design., , and . ICSI (2), volume 6146 of Lecture Notes in Computer Science, page 307-314. Springer, (2010)Feature Selection for siRNA Efficacy Prediction using Natural Computation., and . NaBIC, page 1759-1764. IEEE, (2009)Protein-protein interaction and molecular dynamics analysis for identification of novel inhibitors in Burkholderia cepacia GG4., , , , and . Comput. Biol. Chem., (2016)Predicting liver cancer on epigenomics data using machine learning., , and . Frontiers Bioinform., (2022)