Gang Hu

TL;DR: This work comprehensively characterized intrinsic disorder at proteomic and protein levels from all significant perspectives, including abundance, cellular localization, functional roles, evolution, and impact on structural coverage, and shows that intrinsic disorder is more abundant and has a unique profile in eukaryotes.

TL;DR: A scalable unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function and enables removal of batch effects is introduced.

TL;DR: It is shown that transfer learning across datasets remarkably improves data quality and SAVER-X trains a deep neural network for transfer learning that improves the quality of scRNA-seq data using prior information learnt from existing public studies.

TL;DR: It is demonstrated that APOE and TREM2 risk variants are associated with a significant reduction in CD163-positive amyloid-responsive microglia, highlighting the diverse microglial response in AD and underscore how genetic risk factors influence cellular responses to underlying pathologies.

TL;DR: This work quantified and investigated numerous functional and structural characteristics of the disorder-enriched hub PPIs, including protein binding, structural stability, evolutionary conservation, several categories of functional sites, and presence of over twenty types of posttranslational modifications (PTMs).