Xin Gao

Principal Investigator


Professor of Computer Science
Acting Associate Director, Computational Bioscience Research Center
Deputy Director, Smart Health Initiative
Computer, Electrical and Mathematical Sciences & Engineering Division
King Abdullah University of Science and Technology

Research Interests

  • Machine learning with applicatioons in biology and biomedicine.
  • Computational methodology development in the following example applications:
    • Nanopore sequencing data analysis and applications.
    • Cryo-EM and cryo-ET based molecular 3D structure determination.
    • Biomedical imaging.
    • Big biological data mining and disease embedding.
    • Clinical diagnosis of genetic diseases.
  • more information

Selected Publications

1. H. Kuwahara, and X. Gao. Stable maintenance of hidden switch as a way to increase the gene expression stability. Nature Computational Science. (2021) 1: 62-70.

2. L. Zhou, Z. Li, J. Zhou, H. Li, Y. Chen, Y. Huang, D. Xie, L. Zhao, M. Fan, S. Hashmi, F. AbdelKareem, R. Eiada, X. Xiao, L. Li, Z. Qiu, and X. Gao. A rapid, accurate and machine-agnostic segmentation and quantification method for CT-based COVID-19 diagnosis. IEEE Transactions on Medical Imaging. (2020) 39(8): 2638-2652. 

3. F. Alzahrani, H. Kuwahara, Y. Long, M. Al-Owain, M. Tohary, M. AlSayed, M. Mahnashi, L. Fathi, M. Alnemer, M. Al-Hamed, G. Lemire, K. Boycott, M. Hashem, W. Han, A. Al-Maawali, F. Mzhrizi, K. Al-Thihli, X. Gao, and F. Alkuraya. Recessive deleterious variants in SMG8 expand the role of nonsense-mediated decay in developmental disorders in humans. The American Journal of Human Genetics. (2020) 107(6): 1178-1185.

4. S. Maddirevula, H. Kuwahara, N. Ewida, H. Shaseldin, N. Patel, F. Alzahrani, T. AlSheddi, E. AlObeid, M. Alenazi, H. Alsaif, M. Alqahtani, M. AlAli, H. AlAli, R. Helaby, N. Ibrahim, F. Abdulwahab, M. Hashem, N. Hanna, D. Monies, N. Derar, A. Alsagheir, A. Alhashem, B. Alsaleem, H. Alhebbi, S.  Wali, R. Umarov, X. Gao, and F. Alkuraya. Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnositics. Genome Biology. (2020) 21: 145. 

5. L. Ding, Y. Liu, L. Liu, F. Zhu, Y. Yao, L. Shao, and X. Gao. Approximate kernel selection via matrix approximation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). (2020) 31(11): 4881-4891.

6. J.H. Lam, Y. Li, L. Zhu, R. Umarov, H. Jiang, A. Heliou, F.K. Sheong, T. Liu, Y. Long, Y. Li, L. Fang, R. Altman, W. Chen, X. Huang, and X. Gao. A deep learning framework to predict binding preference of RNA constituents on protein surface. Nature Communications. (2019) 10: 4941.

7. G. Jia, Y. Li, H. Zhang, I. Chattopadhyay, A.B. Jensen, D. Blair, L. Davis, P. Robinson, T. Dahlen, S. Brunak, M. Benson, G. Edgren, N. Cox, X. Gao, and A. Rzhetsky. Estimating heritability and genetic correlations from large health datasets in the absence of genetic data. Nature Communications. (2019) 10: 5508.

8. Y. Li, R. Han, C. Bi, M. Li, S. Wang, and X. Gao. DeepSimulator: a deep simulator for Nanopore sequencing. Bioinformatics. (2018). 34(17): 2899-2908. 

9. Y. Li, S. Wang, R. Umarov, B. Xie, M. Fan, L. Li, and X. Gao. DEEPre: sequence-based enzyme EC number prediction by deep learning. Bioinformatics. (2018). 34(5): 760-769.

10. H. Kuwahara, M. Alazmi, X. Cui, and X. Gao. MRE: a web tool to suggest foreign enzymes for the biosynthesis pathway design with competing endogenous reactions in mind. Nucleic Acids Research. (2016) 44(W1): W217-25.‚Äč


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2009-2010 Lane Fellow, Lane Center for Computational Biology, Carnegie Mellon University, US
2004-2009 Ph.D., David R. Cheriton School of Computer Science, University of Waterloo, Canada
2000-2004 Bachelor of Science, Computer Science and Technology Department, Tsinghua University, China