Xinlian Zhang

The paper evaluates clustering methods for multivariate longitudinal data using a real-world eCDF-Copula resampling framework to address missing data and improve benchmarking.

This paper introduces eCDF-copula, a method for generating synthetic longitudinal tabular data that preserves within- and between-visit dependence structures, outperforming existing methods in resemblance and utility.

The paper introduces a mixed-effects location-scale model to analyze variability in longitudinal actigraphy data, showing that modeling both mean and variability improves understanding of sleep patterns in schizophrenia.

This study identifies the Aquarius/EMB-4 helicase as essential for initiating small RNA-induced co-transcriptional gene silencing in C. elegans by facilitating HRDE-1 complex engagement with nascent transcripts.