cv

Intern

BGI Research

• Multi-Omics

Intern

Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences

• Evolutional genomics

Master

ShanghaiTech University

Computational Biology

• Biology

Bacholar

Shanghai Ocean University

Bioinformatics

• Aquaculture

National Scholarships

Ministry of Education of the People's Republic of China

My 2nd National Scholarship for Master's Degree

National Scholarships

Ministry of Education of the People's Republic of China

My 1st National Scholarship for Master's Degree

PhenoScreen: A Dual-Space Contrastive Learning Framework-based Phenotypic Screening Method by Linking Chemical Perturbations to Cellular Morphology

bioRxiv

PhenoModel is a cutting-edge molecular representation foundation model that integrates cell phenotype data to enhance the characterization of molecules. By leveraging the rich information embedded in cell images, PhenoModel significantly improves performance in various drug discovery tasks, particularly in virtual screening. Based on PhenoModel, we developed an active compound screening pipeline called PhenoScreen to further screen other molecules with similar activities but novel scaffolds according to the known active compounds.

DeepSA: a deep-learning driven predictor of compound synthesis accessibility

J Cheminform

DeepSA is proposed to predict synthesis accessibility of compounds, and has a much higher early enrichment rate in discriminating molecules that are difficult to synthesize. This helps users to select less expensive molecules for synthesis, thus reducing the time for drug discovery and development. You can use DeepSA on a webserver at https://bailab.siais.shanghaitech.edu.cn/deepsa