Poster Session (PSa-144～PSa-166)

[PSa-151] DeSide: A deep learning and single-cell deconvolution method for solid tumors

*Xin Xiong¹, Yerong Liu², Dandan Pu², Zhu Yang³, Zedong Bi⁴, Liang Tian^1,3, Xuefei Li² (1. Department of Physics, Hong Kong Baptist University, Hong Kong, China., 2. CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China., 3. State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China., 4. Lingang Laboratory, Shanghai 200031, China.)

Keywords:cell type deconvolution, solid tumor, RNA-seq, deep learning, single cell