Xing Laboratory

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The Xing Lab is broadly interested in computational biology and genomics of RNA processing and regulation, as well as their applications to human genetics, precision medicine, and cancer immunotherapy.

Mammalian cells generate astonishing regulatory diversity and complex phenotypes from a surprisingly small set of genes. We now know that considerable diversity is achieved by alternative processing and modifications of RNA. The long-term goal of our research is to elucidate alternative isoform complexity in mammalian transcriptomes and proteomes, and to understand how it is generated and its role in the regulation and function of complex genomes.

We develop computational methods and genomic technologies for studying transcriptomic and proteomic complexity in bulk tissues and single cells, and integrate computational and genomic tools to elucidate RNA regulatory networks in health and disease.

Join Us!

Join the Xing Lab

The Xing Lab has openings for motivated undergraduate and graduate students from various scientific disciplines (e.g., biology, medicine, statistics, and engineering) who wish to work at the interface of genomics, bioinformatics and medicine.

Please contact xingyi [at] chop.edutitle="Contact Xing Lab" for more information.

For inquiries of postdoctoral fellow positions, please send a CV, list of publications, and details of three references to xingyi [at] chop.edutitle="Contact Xing Lab".

xingyi [at] chop.edu (Contact Xing Lab)hreflang="en"

Project Highlights

  • Computational methods for transcriptome analysis using second- and third-generation sequencing technologies
  • Genomic technologies and computational methods for analyzing RNA processing and modifications using low-input or single-cell samples
  • Regulatory networks in health and disease using large-scale RNA-seq data and protein-RNA interaction maps
  • Genetic variation and evolution of transcriptome regulation and RNA processing
  • Clinical RNA-seq technologies for disease diagnosis or early detection
  • Multi-omic and clinical data integration for precision oncology and cancer immunotherapy
Leader
Yi Xing

Yi Xing, PhD