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Synthetic chemical drugs, while being efficacious in the clinical management of many diseases, are often associated with undesirable side effects in patients. It is now clear that the need of therapeutic intervention in many clinical conditions cannot be satisfactorily met by synthetic chemical drugs. Since the research and development of new chemical drugs(More)
During an investigation of antitumor substances from Nigella glandulifera Freyn et Sint. (Ranunculaceae) the cytotoxicity of two oleanane triterpene saponins isolated from the seeds of this species, kalopanaxsaponins A and I, was evaluated against HepG2, drug resistant HepG2 (R-HepG2) (two hepatocyte cell lines) and primary cultured normal mouse(More)
Dimensionality reduction is usually involved in the domains of artificial intelligence and machine learning. Linear projection of features is of particular interest for dimensionality reduction since it is simple to calculate and analytically analyze. In this paper, we propose an essentially linear projection technique, called locality-preserved maximum(More)
Lasso-type variable selection has increasingly expanded its machine learning applications. In this paper, un-correlated Lasso is proposed for variable selection, where variable de-correlation is considered simultaneously with variable selection, so that selected variables are uncorrelated as much as possible. An effective iterative algorithm, with the proof(More)
Without constructing adjacency graph for neighborhood, we propose a method to learn similarity among sample points of manifold in Laplacian embedding (LE) based on adding constraints of linear reconstruction and least absolute shrinkage and selection operator type minimization. Two algorithms and corresponding analyses are presented to learn similarity for(More)