Welcome to the Lab of Bioinformatics & Multi-omics @ XJTU
At the interface between Biology and Computer Science, the Xu lab seeks a better understanding of transcriptional regulation during development and disease pathogenesis. Mainly based on high-throughput sequencing technologies, we use the statistical and computational methods combined with experimental approaches to detangle the genetic and epigenetic regulations of transcription, at both the bulk-tissue and single-cell resolutions.
News & Events
Single-cell RNA-sequencing (scRNA-seq) enables the characterization of transcriptomic profiles at the single-cell resolution with increasingly high throughput. However, it suffers from many sources of technical noises, including insufficient mRNA molecules that lead to excess false zero values, termed dropouts. Computational approaches have been proposed to recover the biologically meaningful expression by borrowing information from similar cells in the observed dataset. However, these methods suffer from oversmoothing and removal of natural cell-to-cell stochasticity in gene expression. Here, we propose the generative adversarial networks (GANs) for scRNA-seq imputation (scIGANs), which uses generated cells rather than observed cells to avoid these limitations and balances the performance between major and rare cell populations... [Nucleic Acids Research, Volume 48, Issue 15, 04 September 2020, Page e85]