Xiaomei Li

TACO detects presymptomatic Long COVID by combining causal inference with a foundation model, achieving higher precision with fewer features and no hyperparameter tuning.

This paper reviews computational methods and datasets for understanding Long COVID's mechanisms and developing diagnostic and therapeutic strategies using multi-omics data.

This paper identifies 32 causal genes for Long COVID using a multi-omics framework combining TWMR and CT, revealing novel genetic factors and symptom subtypes.

This study identifies small-molecule ligands for TRIM21, an E3 ligase, demonstrating their ability to degrade nuclear pore complex proteins and induce cell death in cancer cells.

GeneWhisperer enhances manual genome annotation by integrating large language models to assist with curation tasks and improve efficiency.

This paper introduces DGBCox, a stable prediction method for breast cancer prognosis under data distribution shift, showing improved accuracy and stability compared to existing methods.

This paper introduces PAN, a method to create sample-specific gene networks using annotations, improving breast cancer relapse prediction compared to existing methods.

This paper introduces a pseudo-time causality method to identify miRNA-mRNA interactions during biological processes, showing improved performance over existing methods in both single-cell and bulk data.

The paper predicts cellular positions in the Drosophila embryo using scRNA-seq data by benchmarking methods against spatially annotated genes.

This paper introduces scPrognosis, a method using scRNA-seq data to improve breast cancer prognosis by analyzing EMT-related gene expression dynamics, outperforming bulk RNA-seq based methods.

The paper presents methods and tools for predicting cell locations in Drosophila embryos using single-cell transcriptomic data, achieving top results in two sub-challenges.