Objective(s):MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression. They have important roles in kidney development, homeostasis and disease, and participate in the onset and progression of tubulointerstitial sclerosis and end-stage glomerular lesions that occur in various forms of chronic kidney disease (CKD). In the present study, we elucidated the role of microR...

a nonstandard finite difference (nsfd) scheme has been constructed and analyzed for a mathematical model that describes lotka–volterra food web model. this new discrete system has the same stability properties as the continuous model and,on the whole, it preservesthe same local asymptotic stability properties. linearized stability theory and schur–cohn criteria are used for local asymptoticstab...

Though music is fundamentally an aural phenomenon, we often communicate about music through visual means. The paper examines a number of visualization techniques developed for music, focusing especially on those developed for music analysis by specialists in the field, but also looking at some less successful approaches. It is hoped that, by presenting them in this way, those in the MIR communi...

Objective(s): Growing evidences have indicated microRNAs as modulators of tumor development and aggression. On the other hand, a phenomenon known as epithelial-mesenchymal transition (EMT) that indicates a transient phase from epithelial-like features to mesenchymal phenotype is a key player in tumor progression.  In this study, we aimed to assess the potential impacts...

Many studies have investigated misregulation of miRNAs relevant to multiple sclerosis (MS) pathogenesis. Abnormal miRNAs can be used both as candidate biomarker for MS diagnosis and understanding the disease miRNA-mRNA regulatory network. In this comprehensive study, misregulated miRNAs related to MS were collected from existing literature, databases and via in silico prediction. A multi-staged...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...