Modeling and predicting biological dynamic systems and simultaneously estimating the
kinetic structural and functional parameters are extremely important in systems and …

Background Peanut allergy is characterized by the development of IgE against peanut
antigen. Objective We sought to evaluate the evolution of epitope-specific (es) IgE and …

The application of machine learning to longitudinal gene-expression profiles has
demonstrated potential to decrease the assessment gap, between biochemical …

High-dimensional linear classifiers, such as distance weighted discrimination (DWD) and
versions of the support vector machine (SVM), are commonly used in biomedical research to …

Background Despite shortening vasopressor use in shock, hydrocortisone administration
remains controversial, with potential harm to the immune system. Few studies have …

An ordinal scale is commonly used to measure health status and disease related outcomes
in hospital settings as well as in translational medical research. In addition, repeated …

Time-course high-throughput gene expression data are emerging in genomic and
translational medicine. Extracting interesting time-course patterns from a patient cohort can …

We consider a research scenario motivated by integrating multiple sources of information for
better knowledge discovery in diverse dynamic biological processes. Given two longitudinal …

Genomic data sets contain the effects of various unobserved biological variables in addition
to the variable of primary interest. These latent variables often affect a large number of …

With the rapid evolution of high‐throughput technologies, time series/longitudinal high‐
throughput experiments have become possible and affordable. However, the development …