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Xin Gao

Associate Professor, Computer Science 

Computer, Electrical and Mathematical Science and Engineering Division
Center membership : 
Computational Bioscience


Structural and Functional Bioinformatics Group

Affiliations

Education Profile

  • ​​​​​​​​​​Ph.D. University of Waterloo, Canada, 2009
  • B.S. Tsinghua University, 2004

Research Interests

Gao's research lies at the intersection between computer science and biology. His work has two main focuses: 1) developing theory and methodology in the fields of machine learning and algorithms; and 2) solving key open problems in biological and medical fields through building computational models, developing machine-learning techniques, and designing effective and efficient algorithms. In particular, he aims to solve problems that occur along the path from protein amino acid sequences to their three-dimensional structures and functions that ultimately lead to their undesirable expression in complex biological networks.

Selected Publications

  • ​A. Abbas, X. Guo, B. Jing, and X. Gao. An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming. Journal of Biomolecular NMR. (2014). 59(2): 75-86.
  • H. Kuwahara, M. Fan, S. Wang, and X. Gao. A framework for scalable parameter estimation of gene circuit models using structural information. Bioinformatics. (2013). 29(13): i98-i107.
  • B. Xie, B. Jankovic, V. Bajic, L. Song, and X. Gao. Poly(A) motif prediction using spectral latent features from human DNA sequences. Bioinformatics. (2013). 29(13): i316-i325.
  • M. Maadooliat, X. Gao, and J. Huang. Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles. Briefings in Bioinformatics. (2013). 14(6): 724-736.
  • Z. Liu, A. Abbas, B. Jing, and X. Gao. WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering. Bioinformatics (2012), 28(7): 914-920.
  • B. Alipanahi, X. Gao, E. Karakoc, L. Donaldson, A. Gutmanas, C. Arrowsmith, and M. Li. PICKY: a novel SVD-based NMR spectra peak picking method. Bioinformatics. (2009). 25(12): i268-i275.
  • X. Gao, D. Bu, J. Xu, and M. Li. Improving consensus contact prediction via server correlation reduction. BMC Structural Biology, 2009, 9:28.​