2017.09.14 Computational approaches for dissecting tumor-immune interaction

2019-07-07 00:49:37 15






题 目:  Computational approaches for dissecting tumor-immune interaction

报告人李博 博士

Harvard School of Public Health

时 间2017914(周四)13:00-14:00

地 点北京大学老化学楼东配楼101报告厅

主持人: 欧阳颀 教授

摘 要:

  Characterization of the interaction between cancer and immune system is critical to developing novel immunotherapies. Here in this talk, I will present two computational methods we have developed. The first one is Tumor Immune Estimation Resource, or TIMER (https://cistrome.shinyapps.io/timer/), which is a statistical tool for deconvolving different immune cell components in the tumor microenvironment using gene expression data. The second one is called T-cell receptor Repertoire Utilities for Solid Tumor, or TRUST (https://bitbucket.org/liulab/trust), which is a de novo assembler for analyzing the TCR hypervariable sequences using unselected RNA-seq data. Application of both methods to large cancer cohort lead to biological findings with potential clinical applications.


2005-2009 北京大学物理学院,学士学位;

2009-2014 密歇根大学生物信息学,博士学位;

2014年至今 Harvard School of Public Health从事博士后研究。