Dali Han

IDEAL-Age is a deep learning framework that profiles immunological aging at single-cell resolution, showing improved predictive performance and revealing cellular contributions to aging processes.

The paper introduces UCASpatial, an ultra-precision spatial transcriptomics deconvolution algorithm, to improve the identification of immune cell subpopulations and their functional roles in tissue microenvironments.

AutoGenome is an automated deep learning framework for genomic profiling data that uses a residual fully-connected neural network and AutoML to train high-performance models.

This study shows that m6A-mediated cell-cell communication is essential for planarian regeneration, as disrupting m6A methyltransferase leads to regeneration failure.

The paper describes the 2019nCoVR resource, which curates and analyzes SARS-CoV-2 genomes, variants, and haplotypes globally, providing daily updates and integration with literature and databases.