Jiayu Su

Perplexity as a Metric for Isoform Diversity in the Human Transcriptome

The paper introduces perplexity as a metric to quantify isoform diversity in the human transcriptome using long-read RNA-sequencing data, showing it provides interpretable and reproducible measurements.

A computational framework for mapping isoform landscape and regulatory mechanisms from spatial transcriptomics data

This paper introduces SPLISOSM, a framework for analyzing spatial transcriptomics data to detect isoform-level patterns, identifying spatially variable transcript diversity and regulatory relationships in mouse and human brain tissues.

GET: a foundation model of transcription across human cell types

GET is a foundation model that accurately predicts gene expression and regulatory interactions across 213 human cell types using chromatin accessibility and sequence data.

Smoother: A Unified and Modular Framework for Incorporating Structural Dependency in Spatial Omics Data

Smoother integrates positional information into non-spatial models for spatial omics data, enabling accurate imputation, deconvolution, and dimensionality reduction in simulated and real datasets.