Jiguang Wang

CellART: a unified framework for extracting single-cell information from high-resolution spatial transcriptomics

CellART extracts single-cell information from high-resolution spatial transcriptomics data across multiple platforms, demonstrating efficiency and accuracy in cancer datasets.

Accurate and scalable decontamination of imaging-based spatial transcriptomics via optimal transport

CellDot improves spatial transcriptomics by accurately decontaminating transcript assignments using optimal transport, enhancing biological interpretation and spatial pattern recovery.

Lysosomal Dysfunction-Mediated IgG Accumulation Promotes Endothelial Senescence and Lesion Progression in Cerebral Cavernous Malformations

STAT: A multi-agent framework for integrated and interactive spatial transcriptomics analysis

STAT is a multi-agent framework that improves spatial transcriptomics analysis by enabling interactive, transparent, and efficient multi-task analysis across different data resolutions.

Multimodal integration of single cell ATAC-seq data enables highly accurate delineation of clinically relevant tumor cell subpopulations

MAAS integrates multimodal scATAC-seq data to identify clinically relevant tumor subpopulations and improve prognostic prediction.

Genomic Touchstone: Benchmarking Genomic Language Models in the Context of the Central Dogma

Genomic Touchstone evaluates genomic language models across 36 tasks and 88 datasets, revealing insights on model performance, scaling, and pretraining strategies.

Genome-wide Viral Nascent RNA Sequencing Unveils Polymerase Pausing Landscape at Single-nucleotide Precision

The paper introduces TenVIP-seq to study viral nascent RNA synthesis, revealing RdRp pausing patterns and high mutation rates in viral RNA.

Epigenetic reprogramming induced by Acetyl-CoA and SAM depletion is an evolutionarily-ancient path to malignant growth

This study identifies common metabolic and epigenetic changes in fly and human tumors, showing that metabolite depletion drives tumorigenesis across species.

Extensive MET alterations confer clinical response to MET inhibitors in gliomas

This study identifies MET gene alterations in gliomas and shows that these alterations are associated with better response to MET inhibitors.

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression

CNAPE predicts copy number alterations from gene expression data using a machine learning model trained on The Cancer Genome Atlas data, achieving over 90% accuracy for arm-level CNAs.

Drosophila scribble mutant tumors undergo a transition from a growth arrest state to a proliferative state over time

This study shows that Drosophila scrib mutant tumors transition from a growth arrest to a proliferative state over time, suggesting potential for tumor evolution.