Let consider a sample of n individuals with nc controls and nd cases (nc+nd = n) and Y = [y1, . . . , yn] ′ the vector of the observed binary phenotypes. Each gene is a collection of respectively m1 and m2 SNPs. The observed genotypes for gene X1 can be represented by a n×m1 matrix: X1 = [xij ]i∈1...n;j∈1...m1 where xij ∈ {0; 1; 2} is the number of copies of the minor allele for SNP j carried b...

expansins are cell wall proteins that due to changes in ph, causing the expansion of the cell wall .these proteins are causing deformation of walls through loosening hydrogen bonds between the cellulose and polymer matrix microfibrils .in this study, a root specific gene called atexpa18 -that directly affect the formation of root hairs and also its role  have been proved in other parts of the p...

The nuclear matrix appears to play an important role in developmental gene expression during osteoblast differentiation. To better understand this role, we examined nuclear matrix DNA-binding proteins that are sequence-specific and interact with the osteocalcin gene promoter. Multiple protein-DNA interactions involving two distinct nuclear matrix proteins occur within the 5' regulatory sequence...

Mechanical interaction of cells and their surroundings are prominent in mechanically active tissues such as cartilage. Chondrocytes regulate their growth, matrix synthesis, metabolism, and differentiation in response to mechanical loadings. Cells sense and respond to applied physical forces through mechanosensors such as integrin receptors. Herein, we examine the role of mechanical stimulation ...

cialist working in the area under discussion or to individuals involved in very closely related areas of research. Within these limits, both the clinical and basic immunologist will find the first of two of these articles to be extremely useful, while immunochemists will no doubt value all three. The study of histocompatibility antigens is becoming increasingly important since apart from their ...

Motivation: Gene expression data consists of expression level reads for thousands of genes across dozens of experimental conditions, time points, cell types or repeated experiments. The goal of unsupervised modeling of such data is to find some underlying organization, structure or redundancy in the data, such as similarity or dependency between genes or between experiments. Such structure can ...