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Chongle Pan

Chongle Pan

Chongle Pan

Professor of Computer Science and Biomedical Engineering

Email: cpan@ou.edu
Phone: (405) 325-2972
Office: Devon Energy Hall Room 231

Website: www.thepanlab.com/

Education
Ph.D., Computer Science 
University of Tennessee, Knoxville
B.S., Computer Science 
East China Normal University, China

Research Focus

My research spans Computer Science (in the areas of explainable machine learning and parallel computing for biomedical informatics) and Microbiology (in the areas of human microbiomes and environmental microbiomes). In human microbiomes, I am interested in understanding the beneficial impacts of probiotics and prebiotics on human health. In environmental microbiomes, I am interested in developing mechanistic models of wetland sediment communities to predict their emission of greenhouse gases in future climate regimes. Our approaches include computational biology, proteomic stable isotope probing, integrated -omics, and synthetic microbiomes.

Experience and Awards

  • Professor, School of Computer Science, Stephenson School of Biomedical Engineering
  • Associate Professor, School of Computer Science, School of Biological Sciences, University of Oklahoma
  • Senior Research Scientist, Computer Science and Mathematics Division, Oak Ridge National Laboratory

 

Dr. Chongle Pan is an associate professor in the School of Computer Science and the Department of Microbiology and Plant Biology at the University of Oklahoma. Prior to joining OU, he worked as a senior research scientist in the Computer Science and Mathematics Division of Oak Ridge National Laboratory. Dr. Pan has published more than 60 peer-reviewed journal publications and is the corresponding author on 14 publications. He has mentored 6 postdoctoral researchers, 3 of whom then became tenure-track assistant professors of computer science in the U.S. His research focuses on using artificial intelligence and machine learning for knowledge discovery in bioinformatics and developing new high-performance computing algorithms for scalable analytics of big -omics data.

  • Badré, L. Zhang, W. Muchero, J.C. Reynolds, C. Pan (2021) Deep Neural Network Improves the Estimation of Polygenic Risk Scores for Breast Cancer. Journal of Human Genetics, 66(4):359-369
  • C. Wang, P. Calle, N. Ton, Z. Zhang, F. Yan, A.M. Donaldson, N.A. Bradley, Z. Yu, C. Pan, Q. Tang (2021) Deep-learning-aided forward optical coherence tomography endoscope for percutaneous nephrostomy guidanceBiomedical Optics Express12(4):2404-2418
  • A.J. Paul, D. Lawrence, M. Song, S.H. Lim, C. Pan, T.H. Ahn (2019) Using Apache Spark on Genome Assembly for Scalable Overlap-Graph ReductionHuman Genomics 13(Suppl 1):48. doi: 10.1186/s40246-019-0227-1
  • X. Guo, Z. Li, Q. Yao, R.S. Mueller, J. K. Eng, D. L. Tabb, W. J. Hervey, and C. Pan (2018) Sipros Ensemble improves database searching and filtering for complex metaproteomicsBioinformatics  34(5):795-802
  • Q. Yao, Z. Li, Y. Song, S. J. Wright, X. Guo, S. G. Tringe, M.M. Tfaily, L. Paša-Tolic, T. C. Hazen, B. L. Turner, M. A. Mayes, C. Pan (2018) Community Proteogenomics Reveals the Systemic Impact of Phosphorus Availability on Microbial Functions in Tropical SoilNature Ecology and Evolution 2(3):499-509