معرفی
Cuncong Zhong, Ph.D., is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas, where he leads the Zhong Lab in computational biology and bioinformatics. His research focuses on developing accurate and efficient computational methods to tackle biological challenges, with emphasis on non-coding RNA structure and function, metagenomics, cancer genomics, and precision medicine.
Education:
- Ph.D. in Computer Science, University of Central Florida
- M.S. in Computer Science, University of Central Florida
- B.S. in Computer Science and Biotechnology, Huazhong University of Science and Technology
Research Interests:
Dr. Zhong's research spans several key areas in computational biology:
- Computational Biology & Bioinformatics: Developing algorithms and data structures for biological data analysis
- Non-coding RNA: Investigating RNA structural motifs and their functional implications
- Metagenomics: Creating peptide-centric analysis tools for microbial community studies
- Cancer Genomics: Analyzing NGS data to identify cancer-related genetic variations
- Precision Medicine: Applying computational approaches to personalized medicine
Scientific Awards:
- Best Paper Award - IEEE ICCABS 2012 (cover page story)
- Outstanding Thesis Award - University of Central Florida 2013
- Traveling Fellowships - ISBRA 2015, IEEE ICCABS 2012
Teaching & Mentorship:
Dr. Zhong teaches EECS730: Introduction to Bioinformatics, covering topics from sequence alignment to RNA structure prediction. His lab actively recruits motivated students with backgrounds in algorithms, programming, or biology. The lab's website explicitly mentions seeking new students to join their computational biology research efforts.
Research Lab & Collaborations:
The Zhong Lab at the University of Kansas focuses on developing computational tools for biological discovery. They collaborate with experimental biologists to understand fundamental life processes, particularly in areas of RNA biology and microbiome research. The lab has developed several software packages including GRASP, GRASPx, and RNAMotifScanX for various bioinformatics applications.
