IDENTIFICATION OF METHYLATED GENES ASSOCIATED WITH AGGRESSIVE BLADDER CANCER.




A machine learning model for predicting patients with major depressive disorder: A study based on transcriptomic data

BackgroundIdentifying new biomarkers of major depressive disorder (MDD) would be of great significance for its early diagnosis and treatment.Herein, we constructed a diagnostic model of MDD using machine learning methods.MethodsThe GSE98793 and GSE19738 datasets were obtained from the Gene Expression Omnibus database, and the limma R package was us

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Destabilizing protein polymorphisms in the genetic background direct phenotypic expression of mutant SOD1 toxicity.

Genetic background exerts a strong modulatory effect on the toxicity of aggregation-prone proteins in conformational diseases.In addition to influencing the misfolding and aggregation behavior of the mutant proteins, polymorphisms in putative modifier genes Wine Glass may affect the molecular processes leading to the disease phenotype.Mutations in

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