Meet Our Team

Team Overview

Our team consists of 12 dedicated students from WLSA Shanghai Academy, divided into Wet Lab and Dry Lab groups. Led by Yangyi Liu, we collaborated to develop APOPTO-SENSE 2.0, a synthetic biology platform for personalized cancer drug sensitivity testing. The Wet Lab group focused on experimental design and validation, while the Dry Lab group handled modeling and data analysis. Together, we integrated human practices, education, and entrepreneurship to create a comprehensive project.

Wet Lab Group

Yangyi Liu (Team Leader)

Role: Overall coordination, project management, and wet lab supervision. Contributed to synNotch receptor design and plasmid construction.

Yuchuan Wang

Role: Led cell line engineering and transfection experiments. Focused on optimizing HEK293T sensor cell construction.

Xiaolun Tian

Role: Handled apoptosis induction protocols and flow cytometry analysis for HL-60 target cells.

Ziyan Lei

Role: Managed co-culture assays and fluorescence microscopy for synNotch activation detection.

Rongyi Zhu

Role: Assisted in plasmid amplification, extraction, and verification processes.

Jinghe Ren

Role: Supported wet lab safety protocols and data collection for experimental validation.

Dry Lab Group

Jiyun Xu

Role: Led molecular modeling and protein structure predictions using AlphaFold for synNotch fusion.

Zidong Zhang

Role: Developed kinetic simulations with COPASI for signal transduction dynamics.

Zize Zhao

Role: Handled data analysis and curve fitting using Python for dose-response predictions.

Yixuan Tang

Role: Built machine learning models with TensorFlow for drug sensitivity forecasting.

Yihan Xu

Role: Designed network analyses for multiplexing cell death detection simulations.

Jiehan Cheng

Role: Supported software tool development and integration of dry lab results with wet lab data.

Roles and Responsibilities

Our team divided responsibilities based on expertise to ensure efficient progress:

  • Wet Lab Group: Focused on hands-on experiments, including plasmid design, cell engineering, apoptosis induction, and co-culture assays. They ensured rigorous validation through controls and data collection.
  • Dry Lab Group: Handled computational aspects, such as protein modeling, kinetic simulations, data analysis, and predictive modeling, complementing wet lab results for system optimization.
  • Cross-Group Collaboration: All members contributed to human practices, education, and entrepreneurship, with the team leader coordinating integrations like toolkit development and stakeholder feedback.

This structure allowed us to leverage individual strengths while fostering teamwork, resulting in a cohesive project.