Koon‐Kiu Yan

Spotiphy transforms spatial transcriptomics data into single-cell-resolved whole-transcriptome images, revealing novel cellular compositions and spatial domains in Alzheimer's and breast tissue.

scMINER identifies hidden drivers and network rewiring in single-cell RNA-seq data using mutual information, outperforming existing methods in clustering and network inference.

The paper identifies TCF4 and ID3 as key transcription factors driving mammary epithelial stem cell differentiation through single-cell RNA sequencing analysis.

This paper develops a cross-organism framework for enhancer prediction using Drosophila STARR-seq data and supervised machine learning, validated in mouse and human with 153 enhancers.

The paper evaluates reproducibility and quality measures for Hi-C data using real and simulated datasets, showing that specialized methods outperform simple correlation analysis.

MrTADFinder identifies topologically associating domains (TADs) from Hi-C data using network modularity, revealing multi-scale structures and boundary features.

HiC-Spector provides a matrix library for spectral analysis and reproducibility assessment of Hi-C contact maps, distinguishing biological replicates from pseudo-replicates and different cell types.