Kang Hu
Postdoctoral Associate in Biomedical Informatics and Data ScienceAbout
Titles
Postdoctoral Associate in Biomedical Informatics and Data Science
Biography
Kang Hu is a postdoctoral associate at Yale University with a research focus on computational genomics and transposable element biology. He earned his Ph.D. in Computer Science from Central South University in 2025, where he developed HiTE and panHiTE, two bioinformatics frameworks for accurate detection and annotation of transposable elements in population-scale genomic studies. He previously obtained an M.S. in Computer Science from Central South University and a B.S. in Computer Science from Sichuan University.
Last Updated on October 02, 2025.
Appointments
Biomedical Informatics & Data Science
Postdoctoral AssociatePrimary
Other Departments & Organizations
Education & Training
- PhD
- Central South University, Computer Science and Technology (2025)
- MS
- Central South University, Computer Science and Technology (2019)
- BS
- Sichuan University, Electronic Information Engineering (2016)
Research
Overview
- Design efficient algorithms for detecting various transposable elements in genome assemblies.
- Develop accurate classification methods for transposable elements with the help of deep learning methods.
- Identify transposons in large-scale populations and investigate transposon-driven individual variations.
ORCID
0009-0002-8971-3404- View Lab Website
Cheng Lab
Publications
Featured Publications
HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation.
Hu K, Ni P, Xu M, Zou Y, Chang J, Gao X, Li Y, Ruan J, Hu B, Wang J. HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation. Nat Commun 2024, 15: 5573. PMID: 38956036, DOI: 10.1038/s41467-024-49912-8.Peer-Reviewed Original Research
2024
NeuralTE: an accurate approach for Transposable Element superfamily classification with multi-feature fusion
Hu, Kang, et al. "NeuralTE: an accurate approach for Transposable Element superfamily classification with multi-feature fusion." Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. 2024.Peer-Reviewed Original Research
2022
msRepDB: a comprehensive repetitive sequence database of over 80 000 species.
Liao X, Hu K, Salhi A, Zou Y, Wang J, Gao X. msRepDB: a comprehensive repetitive sequence database of over 80 000 species. Nucleic Acids Res 2022, 50: D236-D245. PMID: 34850956, DOI: 10.1093/nar/gkab1089.Peer-Reviewed Original Research
2021
A sensitive repeat identification framework based on short and long reads.
Liao X, Li M, Hu K, Wu FX, Gao X, Wang J. A sensitive repeat identification framework based on short and long reads. Nucleic Acids Res 2021, 49: e100. PMID: 34214175, DOI: 10.1093/nar/gkab563.Peer-Reviewed Original ResearchMultiNanopolish: refined grouping method for reducing redundant calculations in Nanopolish.
Hu K, Huang N, Zou Y, Liao X, Wang J. MultiNanopolish: refined grouping method for reducing redundant calculations in Nanopolish. Bioinformatics 2021, 37: 2757-2760. PMID: 33532819, DOI: 10.1093/bioinformatics/btab078.Peer-Reviewed Original Research
Academic Achievements & Community Involvement
Honors
honor First Prize, Hunan Provincial Graduate Innovation Competition
10/23/2024Regional AwardDetailsChina
Get In Touch
Contacts
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