Xiaochen Bo

MIRACLE enables efficient continual integration of single-cell multimodal data, updating cell atlases with new data without reintegration, and identifies novel cell types and transfers labels across datasets.

This paper benchmarks sequence-function deep learning models using ATAC-seq data, showing that different models and interpretability methods are better suited to specific tasks.

MIDAS integrates and transfers knowledge from single-cell multimodal data by addressing modality alignment and batch effects through a deep probabilistic framework.

The paper investigates structural variations and 3D chromatin organization in pancreatic cancer using SMRT and Hi-C sequencing, revealing their interplay and impact on gene expression and genome stability.

clusterProfiler performs over-representation (Fisher's exact test) and gene set enrichment analyses on Gene Ontology, KEGG, and user-supplied annotations, supporting non-model organisms, multi-condition comparisons, and ggplot2-based visualization.

The paper uses single-molecule long-read sequencing to identify structural variants driving high-altitude adaptation in Tibetans, revealing their role in gene regulation and biological functions.

This study identifies widespread N6-methyladenine (6mA) modification in the human genome, links it to gene expression, and shows its role in cancer by demonstrating reduced 6mA levels in tumors.