3 papers
cs.LG2026
HyCoSeq: Contextual Hyperbolic Representation Learning for Genomic Sequences
Chenhao Zeng, Zhibin Pu, Shufei Ge
Hyperbolic geometry provides a natural inductive bias for genomic representation learning, but existing hyperbolic genomic models primarily use Lorentz convolutions to learn local…
stat.CO2025
A near-exact linear mixed model for genome-wide association studies
Zhibin Pu, Shufei Ge, Shijia Wang
Linear mixed models (LMM) are widely adopted in genome-wide association studies (GWAS) to account for population stratification and cryptic relatedness. However, the parameter esti…
stat.ME2024
A spatial-correlated multitask linear mixed-effects model for imaging genetics
Zhibin Pu, Shufei Ge
Imaging genetics aims to uncover the hidden relationship between imaging quantitative traits (QTs) and genetic markers (e.g. single nucleotide polymorphism (SNP)), and brings valua…