Chenfei Wang

DeSCOPE is a variational autoencoder framework for predicting genetic perturbation responses across multiple omics modalities, outperforming baselines in unseen gene and cell type scenarios.

The paper introduces cFOOT-seq, a method for high-resolution, quantitative detection of TF occupancy across the genome, and demonstrates its application in analyzing TF dynamics and dependencies.

This paper identifies CTHRC1 as a therapeutic target and serum biomarker for aortic dissection, showing it regulates VSMC phenotype and aortic integrity via the ERK1/2 pathway.

ChromBERT, a foundation model pre-trained on ChIP-seq data, generates interpretable representations of context-specific transcription regulatory networks and improves imputation and modeling of regulatory effects in cell types.

SCRIPro infers gene regulatory networks from single-cell and spatial multi-omics data, outperforming existing methods in reconstructing cell type-specific GRNs.

SELINA improves cell type annotation in single-cell RNA-seq by addressing batch effects and rare cell type characterization using domain adaptation and synthetic oversampling.

MetaTiME identifies data-driven meta-components in tumor immune microenvironment scRNA-seq data to annotate cell states and reveal transcriptional regulators.

This paper introduces SCRIP, a method that integrates scATAC-seq and TR ChIP-seq data to infer single-cell TR activity and gene regulation networks, showing improved performance over existing methods.

The paper studies nucleosome dynamics in mouse zygotes after fertilization, identifying factors involved in zygotic genome activation.

STRIDE deconvolves spatial transcriptomics data using single-cell RNA sequencing to estimate cell-type proportions and improve spatial gene and domain identification.

Chromap provides a fast and accurate method for aligning and preprocessing chromatin profiles, outperforming existing tools in speed while maintaining alignment accuracy.

TISCH provides an interactive web resource for visualizing single-cell transcriptomic data of the tumor microenvironment across multiple cancer types.