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A new feature selection algorithm for two-class classification problems and application to endometrial cancer.

, , , , and . CDC, page 2976-2982. IEEE, (2012)

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A sparse Bayesian learning based approach to Inferring Gene Regulatory Networks., , and . GlobalSIP, page 113-116. IEEE, (2013)Optimized prediction of extreme treatment outcomes in ovarian cancer., , , , , , and . CDC, page 1254-1258. IEEE, (2015)Inferring weighted and directed gene interaction networks from gene expression data using the phi-mixing coefficient., , , , and . GENSiPS, page 168-171. IEEE, (2012)Inferring Genome-Wide Interaction Networks Using the Phi-Mixing Coefficient, and Applications to Lung and Breast Cancer., , , , , and . IEEE Trans. Mol. Biol. Multi Scale Commun., 4 (3): 123-139 (2018)A novel application of mixing coefficients for reverse-engineering gene interaction networks., , , , and . Allerton Conference, page 1461-1466. IEEE, (2012)Robust state estimation via twisting observer., and . Autom., (February 2024)bLARS: An Algorithm to Infer Gene Regulatory Networks., and . IEEE ACM Trans. Comput. Biol. Bioinform., 13 (2): 301-314 (2016)Sparse Feature Selection for Classification and Prediction of Metastasis in Endometrial Cancer: Extended Abstract., , , , , , , and . BCB, page 522-524. ACM, (2016)Inferring Gene Regulatory Networks with Sparse Bayesian Learning and phi-mixing coefficient., and . ECC, page 1510-1515. IEEE, (2014)A new feature selection algorithm for two-class classification problems and application to endometrial cancer., , , , and . CDC, page 2976-2982. IEEE, (2012)