Ha T.H. Vu

MUTUAL enables cross-modality analysis between transcriptome and chromatin by learning a shared RNA-ATAC space from multiome data without refitting.

The paper integrates multiple scRNA-seq datasets to create a comprehensive atlas of human pancreatic islets, identifying 13 cell populations and providing a resource for diabetes research.

The paper constructs a healthy human pancreas reference atlas to contextualize disease states and benchmark models.

The paper uses donor-matched iPSC-derived FAPs to show that T2D GWAS signals are enriched in adipogenic FAP subtypes under high-insulin exposure.

The paper uses long-read sequencing to profile native 5hmC and 5mC in human neurons, showing 5hmC enrichment in transcribed regions and enhancers.

The paper compares chromatin accessibility and gene regulatory networks in invasive trophoblast cells between rat and human to identify conserved regulatory mechanisms.

The paper introduces an unsupervised contrastive learning method for ATAC-seq peak calling that outperforms existing methods using replicates and annotations.

This study identifies novel regulators of placental development by analyzing time series RNA-seq data and gene interaction networks in mouse fetal placenta.

The paper uses GOMAP to annotate gene functions across 18 crop plant genomes, showing that these annotations can recover known phylogenetic relationships, supporting comparative functional genomics.