Yuqi Cheng

This paper constructs sex-specific lifespan brain charts using neuroimaging data from 59,915 individuals, revealing dynamic sex differences in brain development and improving detection of neuropsychiatric abnormalities.

This study examines how localized evolutionary changes affect ancestral state reconstruction and shows that tree partitioning can reduce errors in these reconstructions.

EpiPack improves scATAC-seq analysis by integrating heterogeneous features and detecting perturbed cell types and states through transfer learning and graph-based modeling.

scBalance is a sparse neural network framework for cell type annotation in scRNA-seq data, showing strong performance on both common and rare cell types across large datasets.

TAPE deconvolves bulk RNA-seq data into cell-type fractions and gene expression using a deep autoencoder, showing better performance and robustness compared to existing methods.

CLEAR is a self-supervised contrastive learning framework for scRNA-seq that improves clustering, batch correction, and pseudo-time inference by reducing technical noise and heterogeneity.