Qing Li

This study shows FLASH X-rays preserve neutrophil chromatin, reducing NET formation and enhancing antitumor immunity when combined with anti-PD-1 therapy.

The paper uses deconvolution to identify cell-type-specific DNA methylation and gene expression associations with colorectal cancer risk, finding 178 CpG sites and 68 genes across 26 new loci.

This study integrates large-scale omics and electronic health records to identify risk proteins and drugs for cancer prevention, finding 101 novel proteins and three drugs associated with reduced colorectal cancer risk.

The paper introduces AE-TWAS, a method that improves genotype-phenotype association studies by transforming transcriptome data with autoencoders to enhance expression heritability and TWAS performance.

This study introduces transTF-TWAS, a method that integrates transcription factor-linked trans-located variants into transcriptome-wide association analyses to improve disease risk gene discovery.

This paper introduces edLMM, a method that detects low-effect genetic variants using moderate sample sizes, improving missing heritability estimation.

IMAS, a statistical method, uses image-derived phenotypes from the UK Biobank to discover genetic associations with four brain disorders, revealing a common cerebellar mechanism.

The paper introduces cLD, a statistic for measuring rare-variant linkage disequilibrium between genomic regions, and shows it identifies novel genomic interactions and associations.

rvTWAS integrates gene expressions with rare variant sequences to identify gene-trait associations in psychiatric disorders.

XA4C identifies Critical genes using explainable autoencoders, revealing novel biological insights in cancer gene expression data.

The paper applies transfer learning to adapt a general-purpose model to a specific domain using limited data, demonstrating improved performance in breast cancer-related tasks.

This study identifies nkx3.1-expressing precursors in zebrafish that differentiate into brain pericytes and shows their regulation by cxcl12b-Cxcr4 signaling.

The paper constructs a high-density genetic map for Coix lacryma-jobi using SLAF-seq, identifying 3,605 markers across 10 linkage groups with an average distance of 0.45 cM.

The paper introduces XAE4Exp, an explainable autoencoder for gene expression data, identifying non-differentially expressed genes and cancer-related pathways using TCGA data.

This paper shows that combining feature selection and aggregation in GReX limits TWAS power and adaptability, especially with low expression heritability.

kTWAS combines TWAS feature selection with SKAT kernel methods to improve statistical power and identify novel disease-associated genes.

The paper introduces ILMM, a statistical model that integrates genetic interactions into genotype-phenotype association mapping, revealing 3D-genetic basis of ASD and 3D-eQTLs using whole genome and transcriptome sequencing data.

This paper compares the power of GWAS, TWAS, and a hypothetical real expression protocol to determine when TWAS is effective and when GWAS is better.