David Ming Lin

Ultra-fast sample-to-sequencing workflow for clinical diagnostics using micropillars

This paper introduces an integrated microfluidic workflow for Oxford Nanopore sequencing that reduces hands-on time and sample loss while enabling high-quality library preparation from small sample volumes.

Kontextual: Reframing analysis of spatial omics data reveals consistent cell relationships across images

Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data

BIDCell improves subcellular spatial transcriptomics segmentation by combining self-supervised learning with biologically informed loss functions, outperforming existing methods across multiple tissue types.

Characterization of cell-cell communication in COVID-19 patients

The paper characterizes cell-cell communication patterns in COVID-19 patients to identify differences between moderate and severe disease outcomes using single-cell RNA-seq data.

Cepo uncovers cell identity through differential stability

Cepo identifies cell identity by analyzing differentially stable genes from scRNA-seq data, improving cell-type characterization and spatial mapping.

Investigating higher order interactions in single cell data with scHOT

The paper introduces scHOT, a method to detect changes in higher order gene interactions in single-cell data, demonstrating its application in liver development and spatial gene correlation patterns.

Evaluating stably expressed genes in single cells

This study evaluates stably expressed genes (SEGs) in single cells using a computational framework and finds they are more stable than traditional housekeeping genes across species.