Background The analysis of gene expression from time series underpins many biological
studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) …

Understanding the regulatory mechanisms that are responsible for an organism's response
to environmental change is an important issue in molecular biology. A first and important …

Motivation: Although widely accepted that high-throughput biological data are typically
highly noisy, the effects that this uncertainty has upon the conclusions we draw from these …

Motivation: Recent advances in high-throughput sequencing (HTS) have made it possible to
monitor genomes in great detail. New experiments not only use HTS to measure genomic …

Motivation: Identifying the set of genes differentially expressed along time is an important
task in two-sample time course experiments. Furthermore, estimating at which time periods …

Motivation: Time course data are often used to study the changes to a biological process
after perturbation. Statistical methods have been developed to determine whether such a …

Recently, complex network-based approaches are shown to be efficient for spatial analysis
of rainfall variation. One of the most critical limitations of correlation-based networks is using …

Motivation: Time-course gene expression datasets provide important insights into dynamic
aspects of biological processes, such as circadian rhythms, cell cycle and organ …

Background Time course gene expression experiments are an increasingly popular method
for exploring biological processes. Temporal gene expression profiles provide an important …

This paper focuses on the problem of time series forecasting using the Gaussian process
models. The Gaussian process model is a nonparametric model and the output of the model …