Our major research interest concerns the development of statistical and machine learning methods and softwares for computational biology. I am particularly interested in complex biological data modeling, such as high-throughput genomic data, network biology, population genomics and related evolutionary problems. Currently, my research projects are mainly focus on following topics:
  • computational genomics
  • network biology
  • population genomics
  • machine learning


  • 开发和优化针对植物基因组的高质量基因组组装技术;
  • 发展新的算法用于发现基因中的突变、重组、基因拷贝数变异等遗传变异;
  • 发展新的模型用于RNAseq、表观遗传学、chi-seq、单分子测序数据的分析;
  • 构建机器学习模型对上万种植物进行分类鉴定;
  • 大规模基因组计算的云平台构建。


  • Sclust:  A C++/R package for inference of subclonal populations in cancer genomes using smoothing splines.
  • FrSVM:  an R program, short of Filter by highly ranked gene for Support Vector Machine, for microarray classification.
  • netClass: An R package for network-Based microarray Classification