A simple interpretation of two stochastic processes subject to an independent death process.
A stochastic death pairing process.
A Stochastic Solver of the Generalized Born Model
A stochastic generalized Born (GB) solver is presented which can give predictions of energies arbitrarily close to those that would be given by exact effective GB radii, and, unlike analytical GB solvers, these errors are Gaussian with estimates that can be easily obtained from the algorithm. This method was tested by computing the electrostatic solvation energies (ΔGsolv) and the electrostatic binding energies (ΔGbind) of a set of DNA-drug complexes, a set of protein-drug complexes, a set of protein-protein...
An asymptotic test for Quantitative Trait Locus detection in presence of missing genotypes
We consider the likelihood ratio test (LRT) process related to the test of the absence of QTL (a QTL denotes a quantitative trait locus, i.e. a gene with quantitative effect on a trait) on the interval representing a chromosome. The originality is in the fact that some genotypes are missing. We give the asymptotic distribution of this LRT process under the null hypothesis that there is no QTL on and under local alternatives with a QTL at on . We show that the LRT process is asymptotically...
Application of the adaptive center-weighted vector median framework for the enhancement of cDNA microarray images
In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing the sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of the so called gene chips. We demonstrate...
Applications of topology to DNA
The following is an expository article meant to give a simplified introduction to applications of topology to DNA.