Guohua Wang

SVPG improves structural variant detection using pangenome references and accelerates pangenome graph construction from long-read data.

This paper introduces SomaSV, a hybrid sequencing framework that improves somatic structural variant detection accuracy while reducing costs by combining long- and short-read data.

Polus improves DNA storage reliability and efficiency by using a Transformer-based platform to reduce sequencing coverage and errors.

This paper introduces HINS, a deep-learning method that predicts immune checkpoint blockade response using HLA-mediated immunogenic neoantigen scores, achieving high accuracy in identifying responders.

CTDP identifies disease-associated cell types using scRNA-seq by integrating Lasso-regularized logistic regression and permutation testing, outperforming existing methods in accuracy and robustness.

THLANet predicts TCR-pHLA binding using deep learning, outperforming existing methods and providing structural insights into TCR-antigen interactions.

GeoGAT-site predicts protein-protein interaction sites using a geometric graph attention network, achieving high accuracy and efficiency compared to existing methods.

CanASM identifies and annotates allele-specific DNA methylation in 31 cancer types, providing regulatory annotations and tools for analyzing epigenetic regulation in cancer.

The paper introduces cuteSV2, a long-read-based method for accurate structural variant regenotyping, outperforming existing methods in benchmarking.

HiFiCCL improves ultra-low-coverage genome assembly using high-fidelity long-reads, enhancing structural variant detection and pangenome construction in human and plant datasets.

scKEPLM integrates a biology knowledge graph into single-cell transcriptome pre-training to improve gene and cell representation, achieving state-of-the-art performance in multiple downstream tasks.

This paper introduces scpDeconv, a deep learning method for deconvolving cell type mixtures in proteomic data, showing improved performance across species and technologies.

The paper compares transcriptomic responses in zebrafish following rod photoreceptor or bipolar cell loss, identifying cell-specific and shared regenerative gene programs and immune-related regulators.

PlantCADB compiles and annotates chromatin accessibility data from 37 plant species, providing tools to study regulatory networks and genetic mechanisms in development, stress responses, and evolution.

This paper introduces Asset, a tool to evaluate genome assemblies using long-range data, demonstrating its ability to detect structural misassemblies in human, goat, and fish genomes.

The paper identifies neuroprotective compounds for retinitis pigmentosa using cross-species drug screens in zebrafish and mouse models, finding additive effects in some combinations.

The paper withdraws its manuscript due to the need for further experimental validation of its conclusions.

This study identifies gene regulatory networks controlling proliferative and neurogenic competence in retinal Muller glia.

This study shows that neuronal EZH2 regulates neuronal morphogenesis and cognitive behavior in mice by controlling gene expression and dendritic spine density.