Computational drug repositioning is an effective way to find new indications for existing
drugs, thus can accelerate drug development and reduce experimental costs. Recently …

Deep learning is evolving in nutritional epidemiology to address challenges including
precise nutrition and data-driven disease modeling. Fermented dairy products consumption …

The single-cell multiomics technologies provide an unprecedented opportunity to study the
cellular heterogeneity from different layers of transcriptional regulation. However, the …

Advances in single-cell biotechnologies simultaneously generate the transcriptomic and
epigenomic profiles at cell levels, providing an opportunity for investigating cell fates …

Technological advances have enabled us to profile multiple molecular layers at
unprecedented single-cell resolution and the available datasets from multiple samples or …

Data from the single-cell assay for transposase-accessible chromatin using sequencing
(scATAC-seq) are now widely available. One major computational challenge is dealing with …

Background Accurately deciphering clonal copy number substructure can provide insights
into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles …

Motivation The advancement in technologies and the growth of available single-cell
datasets motivate integrative analysis of multiple single-cell genomic datasets. Integrative …

Background Accurate and efficient cell grouping is essential for analyzing single-cell
transcriptome sequencing (scRNA-seq) data. However, the existing clustering techniques …

Poor study reproducibility is a concern in translational research. As a solution, it is
recommended to increase sample size (N), ie, add more subjects to experiments. The goal …