Kui Wang

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 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: A method for prediction of helix/strand content from primary protein sequences that is fundamentally different from currently available methods and has much better accuracy when compared with other existing methods, in contrast to other reported results that often target small sets of specific protein types, such as globular proteins.

TL;DR: Using structural human proteome and a novel algorithm for inverse ligand binding prediction, ILbind, a comprehensive set of 100+ putative partners of CSA are determined and it is empirically show that predictive quality of ILbind is better compared with other available predictors for this compound.

TL;DR: This work proposes a consensus that combines (and outperforms) the two complementary approaches implemented by FINDSITE and SMAP, and demonstrates that these methods successfully find distant targets that belong to structurally different folds compared to the proteins in the input complexes.