Correlation and association analyses are one of the most widely used statistical methods in
research fields, including microbiome and integrative multiomics studies. Correlation and …

Biological processes underlying health and disease are inherently dynamic and are best
understood when characterized in a time-informed manner. In this comprehensive review …

Motivation Recent microbiome association studies have revealed important associations
between microbiome and disease/health status. Such findings encourage scientists to dive …

Background The human microbiome is inherently dynamic and its dynamic nature plays a
critical role in maintaining health and driving disease. With an increasing number of …

Single-cell transcriptional and epigenomics profiles have been applied in a variety of tissues
and diseases for discovering new cell types, differentiation trajectories, and gene regulatory …

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

The era of high-throughput data generation enables new access to biomolecular profiles
and exploitation thereof. However, the analysis of such biomolecular data, for example …

Discovering patterns in time-course genomic data can provide insights on the dynamics of
biological systems in health and disease. Here, we present a Platform for Analysis of Time …

We present a new statistical method using longitudinal gene expression to predict
quantitative outcomes of patients. Through simulations and application on a dataset of burn …

Biological systems are dynamic in nature, where time‐lagged correlations are commonly
observed. Motivated by the problem of integrating longitudinal high‐dimensional datasets …