Yiming Yang

This study uses dynamic caging to link live-cell behavior with transcriptional responses across perturbations, revealing new insights into immune and inflammatory gene regulation.

The paper develops a framework to decode TLS maturation in NSCLC using spatial omics data and deep learning, identifying two distinct spatial ecosystems linked to patient outcomes.

This study presents the genome sequence of Vitis amurensis and identifies genes and genomic features related to cold resistance, disease resistance, and sex determination in grapes.

SCHAF generates spatially resolved single-cell transcriptomes from H&E histology images using vision transformers and adversarial learning, showing good agreement with ground-truth data.

This paper introduces a data-driven quality control framework for single-cell transcriptomics that improves cell retention and biological insight compared to conventional methods.

This study creates a single-cell and spatial atlas of autopsy tissues from COVID-19 patients, revealing altered cellular responses and potential therapeutic targets.

Cumulus is a cloud-based framework for analyzing large-scale sc/snRNA-seq data, improving efficiency and scalability while maintaining result quality.

The paper introduces a method to multiplex single-nucleus RNA-seq using barcoded antibodies, reducing costs and enabling large-scale studies.