Xi Fu

The paper identifies p53-hormone receptor regulatory grammars distributed by Alu elements in mammary and muscle cells, with implications for breast cancer and muscle aging.

This study uses Cas12a-based knockout screens to identify genetic interactions in the DNA damage response, revealing synthetic lethal and buffering interactions with therapeutic implications.

Chromnitron predicts protein-DNA binding landscapes across cell types and proteins using multimodal learning, revealing new regulators of T cell exhaustion and dynamic shifts during neurogenesis.

Genomic Touchstone evaluates genomic language models across 36 tasks and 88 datasets, revealing insights on model performance, scaling, and pretraining strategies.

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

The paper identifies noncoding genetic variants associated with Hirschsprung disease using a framework that captures multi-granular regulatory element perturbations.