Xiaodong Lü

This paper introduces LongFUSE, a tool for detecting fusion genes in single-cell long-read RNA sequencing data, showing improved accuracy over existing methods.

This study identifies NF90 as a coactivator of EZH2's polycomb-independent transactivation function in prostate cancer, promoting cell growth and poor clinical outcomes.

This study identifies NKX2-1-driven epigenetic and 3D chromatin remodeling as key to neuroendocrine prostate cancer progression and reveals CBP/p300 inhibitors as potential therapeutic targets.

The paper presents a LINCS Microenvironment perturbation dataset cataloging transcriptional, proteomic, epigenomic, and phenotypic responses of MCF10A cells to six ligands, enabling integrative analysis of molecular and phenotypic changes.

This study evaluates deconvolution methods for gene expression data using an open innovation competition and finds that random forest regression outperforms other approaches in accuracy and reproducibility.

The paper develops an in-vitro gene expression screening method to predict chemical carcinogenicity and genotoxicity using HepG2 cells and machine learning models.

The paper creates a proteomic resource profiling 90 drugs in six cell lines, revealing cell-specific responses and enabling integration with transcriptional data to identify therapeutic opportunities.

The paper introduces the L1000 platform, a high-throughput gene expression profiling method, and reports 1.3 million perturbational profiles expanding the Connectivity Map for drug mechanism discovery and functional annotation.