Welcome to Bin Duan Lab

Laboratory of Shanghai Center for Systems Biomedicine

Laboratory of Shanghai Center for Systems Biomedicine

Shanghai Jiao Tong University

About the lab

Our lab focuses on applying machine learning and artificial intelligence to systematically characterize key genotypes, molecular phenotypes, and clinical phenotypes within the tumor microenvironment. Through a systems biology approach, we aim to uncover the relationships among these factors to advance precision oncology. Here are our main research directions:

  1. Characterization and prediction of key molecular phenotypes;
  2. Analysis of the tumor microenvironment;
  3. Inference of associations between genotype, molecular phenotype and clinical phenotype.

We are looking to recruit postdoctoral fellow, Ph.D. student, and Master’s student from bioinformatics, computational biology, and mathematics, as well as several interns. If you are interested, please send your resume to binduan@sjtu.edu.cn.

Interests
  • Computational Biology
  • Tumor Microenvironment
  • Artificial Intelligence

Meet the team

Principal Investigator

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Bin Duan (段斌)

Principal Investigator (PI)

Research Overview

Inference of Genotype-Molecular Phenotype-Clinical Phenotype Associations

Inference of Genotype-Molecular Phenotype-Clinical Phenotype Associations

Our research integrates genomic, molecular, and clinical data to infer the relationships between these different layers of tumor biology. We focus on identifying tumor biomarkers, understanding tumor evolution, and performing prognostic analysis, all of which are essential for early diagnosis, targeted therapy, and individualized patient prognosis.

Analysis of the Tumor Microenvironment

Analysis of the Tumor Microenvironment

We aim to explore the immune and microbiome microenvironments of tumors, investigating their composition and function, as well as their impact on tumor development. By integrating multi-omics data, we seek to reveal how the tumor microenvironment influences cancer progression.

Characterization and Prediction of Key Molecular Phenotypes

Characterization and Prediction of Key Molecular Phenotypes

This includes the systematic analysis and prediction of important molecular features, such as tumor hallmarks, cell types, cell states, and spatial domains, which serve as the basic functional units to characterize tumor cells.

Recent Publications

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(2024). PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization. Nucleic Acids Research. (IF: 16.97).

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(2024). Single-cell omics: experimental workflow, data analyses and applications. Science China Life Science. (IF: 10.38,封面文章).

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(2024). Multi-slice spatial transcriptome domain analysis with SpaDo. Genome Biology 25(1): 73. (IF: 12.3).

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(2023). Personalized tumor combination therapy optimization using the single-cell transcriptome. Genome Medicine 15(1): 105 (IF: 12.3).

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(2022). Privacy-preserving integration of multiple institutional data for single-cell type identification with scPrivacy. Science China Life Science: 1-13. (IF: 10.38).

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