Fan Yang

UniPert-G2CP transfers genetic perturbation insights to chemical perturbation modeling, enabling efficient in silico drug screening with reduced data costs.

MolSpecFlow bridges the gap between molecules and mass spectra using a hybrid flow matching model, achieving state-of-the-art results in de novo generation and spectral simulation.

This paper introduces scTranslator, a pre-trained large generative model that translates single-cell transcriptomes to proteomes, showing accuracy and utility in multiple downstream tasks.

CD-GPT is a foundation model that captures sequence relationships between DNA, RNA, and proteins, performing well in predictive and generative tasks across molecular types.

This paper introduces tFold-Ab and tFold-Ag for fast and accurate prediction of antibody and antibody-antigen complex structures, showing improved speed and performance over AlphaFold-Multimer.

STOmicsDB provides a database for spatial transcriptomics data with tools for dataset visualization, publication search, and data archiving.

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 introduces scPROTEIN, a deep graph contrastive learning framework for single-cell proteomics that addresses uncertainty, denoising, batch effects, and embedding learning.

Spatial-ID improves cell type annotation in spatial transcriptomics by combining transfer learning and spatial embedding, outperforming existing methods on public datasets.

scBERT is a pre-trained deep learning model for cell type annotation in single-cell RNA-seq data, showing improved performance and robustness compared to existing methods.

CDCP is a platform for sharing and analyzing single-cell datasets, offering visualization and analysis tools for researchers.

The paper introduces MLA-GNN, a graph neural network that discovers clinically interpretable pathway-level biomarkers by integrating multi-level graph features and a saliency mechanism, achieving state-of-the-art results on transcriptomic and proteomic data.