The development and progression of cancer diseases characterize the genomic instability
that frequently results in genomic alternations including copy number gains or losses …

The availability of the next generation sequencing (NGS) technology in today's biomedical
research has provided new opportunities in scientific discovery of genetic information. The …

Array-based CGH experiments are designed to detect genomic aberrations or regions of
DNA copy-number variation that are associated with an outcome, typically a state of disease …

This paper presents a general half quadratic framework for simultaneous analysis of the
whole array comparative genomic hybridization (aCGH) profiles in a data set. The proposed …

Abstract Bayesian computations with Hidden Markov Models (HMMs) are often avoided in
practice. Instead, due to reduced running time, point estimates–maximum likelihood (ML) or …

In this article a flexible Bayesian non-parametric model is proposed for non-homogeneous
hidden Markov models. The model is developed through the amalgamation of the ideas of …

Hidden semi-Markov models are effective at modelling sequences with succession of
homogenous zones by choosing appropriate state duration distributions. To compensate for …

High-density single-nucleotide polymorphism (SNP) microarrays provide a useful tool for the
detection of copy number variants (CNVs). The analysis of such large amounts of data is …

DNA copy number alterations (CNAs), including amplifications and deletions, can result in
significant changes in gene expression and are closely related to the development and …

Gene copy number (GCN) changes are common characteristics of many genetic diseases.
Comparative genomic hybridization (CGH) is a new technology widely used today to screen …