Zhihan Liu

PoolParty: streamlined design of DNA sequence libraries in Python

PoolParty is a Python package that simplifies the design of DNA sequence libraries for assays like DMS and MPRA, offering a structured and reproducible approach.

Lineage-aware stochastic modeling reveals gene-expression dynamics in development and disease

LaVOUS models gene-expression dynamics along cell lineages, identifying lineage-associated changes in cancer, B cells, and brain development.

Genetic background shapes AI-predicted variant effects

This study introduces pVEP, a framework showing how genetic background affects AI predictions of variant effects, revealing variant effects vary across haplotypes.

Inference of chromosome selection parameters and missegregation rate in cancer from DNA-sequencing data

This paper introduces an algorithm to infer chromosome selection parameters and missegregation rates in cancer using DNA-sequencing data, showing it works well with small datasets.

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

DosaCNV predicts gene haploinsufficiency and deletion pathogenicity using deep multiple-instance learning, outperforming existing methods by integrating gene-level features.