Activities
PROFESSIONAL EXPERIENCE
02/2023 – Present
Lead Bioinformatics Research Scientist, Center for Applied Bioinformatics, St. Jude Children’s Research Hospital
12/2022 – 02/2023
Senior Bioinformatics Research Scientist, Center for Applied Bioinformatics, St. Jude Children’s Research Hospital
10/2022 – 12/2022
Assistant Professor of Bioinformatics Research in Pediatrics, Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine
08/2021 – 10/2022
Senior Bioinformatics Analyst, Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine
03/2019 – 08/2021
Postdoctoral scholar, Department of Medicine, University of Chicago
08/2015 – 08/2018
Postdoctoral scholar, College of Veterinary Medicine, Missssippi State University
04/2013 - 06/2014
Visiting scholar, Department of Botany, Miami University
RESEARCH INTERESTS
- Computational methods of single cell sequencing data
- Single cell sequencing data interpretation and visualization
- Genetics and Evolution methods and their application
- Biological/medical data interpretation and visualization
- Bio-statistical methods and their application
EDUCATION
Xiamen University, Xiamen, China, 2011 - 2015
Ph.D.
System Engineering/Bioinformatics
Xi’an Jiaotong University, Xi’an, China, 2009 - 2011
M.S.
Control Engineering/Natural Language Processing
Xi’an Jiaotong University, Xi’an, China, 2005 - 2009
B.S.
Automation
CONTACT
Advanced Research Center - St. Jude Children's Research Hospital
262 Danny Thomas Place
Memphis, TN, 38105
USA
Email: lei.li[at]stjude.org or leilioxford[at]gmail.com
RECENT PROJECTS
HTOreader: hybrid single cell demultiplexing strategy that increases both cell recovery rate and calling accuracy.
VGenes: an integrated graphical tool for efficient, comprehensive and multimodal analyses of massive B-cell repertoire sequences.
Librator: a platform for optimized sequence editing, design, and expression of influenza virus proteins.
LinQ-View is a joint single cell analysis strategy that could integrate information from both transcriptome and surface protein markers for cell heterogeneity identification.
Cookie: Selecting representative samples from single cell atlas using k-medoids clustering.
