Tianzhou Ma

FM-GPT is a Bayesian fine mapping method that identifies causal genes in phenome-wide transcriptome-wide association studies, improving accuracy and reducing false positives.

This paper identifies systematic prediction bias in aging clocks and introduces a constrained optimization framework to improve calibration and downstream inference.

The paper introduces CAR-NET, a framework for inferring non-coding RNA regulatory networks using transcriptomic data and curated databases, showing its effectiveness in simulations and case studies.

The paper evaluates test-retest reliability of brain imaging metrics across multiple sites and scanners, finding significant differences in reliability between scanner types.

The paper introduces a method to analyze voxel-wise genome-wide associations and identifies genetic loci influencing white matter integrity in the corpus callosum.

The paper analyzes brain functional connectomes in 40,000 individuals to identify aging-related network changes, finding two motor-related subnetworks with age-related declines in functional connectivity.

The paper examines how APOE4 modifies the effect of plasma LDL on white matter integrity in older adults, finding a significant moderation effect.

The paper introduces a screening method to identify genome-wide epigenetic regulators of gene expression by reducing dimensionality in both predictors and responses.

CAMO evaluates omics congruence between model organisms and humans by analyzing differential analysis, concordance, pathway investigations, and subnetwork detection.

This paper introduces a new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures and finds it outperforms existing methods in sensitivity, bias, and false discovery rate.

This paper introduces a novel ℓ0 graph norm shrinkage algorithm for genetic fine-mapping, demonstrating improved sensitivity and reduced false positives in identifying causal variants for nicotine dependence.

The paper evaluates vertical and horizontal pleiotropy pathways linking genetic variants, white matter integrity, and nicotine dependence using UK Biobank data.

The paper introduces CPI, a tool for integrating multiple transcriptomic studies to identify consensual and differential pathway enrichment patterns, and applies it to psychiatric disorder data.

The paper introduces a link prediction model using ERGM with outcome misclassification to handle incomplete network data, showing improved performance on social and brain networks.