Changhui Yan

Assistant Professor

Phone:  701-231-8182

Office: IACC 258 B3

Email: Changhui.Yan@ndsu.edu

Office Hours: 1:45pm-3:00pm T, Th

 

 

Announcement:  Research assistants wanted!  Requirements: self-motivated, hard-working, proficient in programming in C++/Java. Contact me for details.

 

Education:

Iowa State University, PhD (2005), Majors: Computer Science; Bioinformatics and Computational Biology;

Teaching:

CSci 374 Computer Organization and Architecture

CSci 732 Introduction to Bioinformatics

CSci 759 Computational Methods in Bioinformatics

Research Topics:

My research mainly focuses on the development of machine learning algorithms to solve specific bioinformatic problems, such as identification of protein functional sites, protein function/structure prediction, gene finding, and sequence classification. Other topics that I am interested in include protein folding, protein docking, gene expression analysis, phylogenetic inference and protein interaction network.

Research tools developed:

For details, please visit the home page of my research group.

 

Recent Refereed Journal Articles

1.  Alvarez, M. and Yan, C. A graph-based semantic similarity measure for the gene ontology. Journal of Bioinformatics and Computational Biology 2011, 9(6): 1–15.

2.  Alvarez, M., Qi, X. and Yan, C. A shortest-path graph kernel for estimating gene product semantic similarity. Journal of Biomedical Semantics 2011, 2:3.

3.  Hu, J. and Yan, C. A Comparative Analysis of Protein Interfaces. Protein Pept. Lett. 2010;17(11):1450-1458.

4.  Yan, C. and Luo, J. An Analysis of Reentrant Loops. Protein J. 2010, 29(5):350-354.

5.  Hu, J. and Yan, C., A tool for calculating binding-site residues on proteins from PDB structures. BMC Struct Biol. 2009, 9:52.

6.  Ju, W., Shan, J., Yan, C., and Cheng, H. Discrimination of disease-related non-synonymous single nucleotide polymorphisms using multi-scale RBF kernel fuzzy support vector machine. Pattern Recognition Letters 2009, 30:391-396.

7.  Hu, J. and Yan, C. A Method for discovering transmembrane beta-barrel proteins in gram-negative bacterial proteomes. Computational Biology and Chemistry 2008 32:298-301.

8.  Hu, J. and Yan, C. Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information BMC Bioinformatics 2008, 9:297.

9.  Yan, C., Hu, J. and Wang, Y. Discrimination of outer membrane proteins using a K-nearest neighbor method. Amino Acids 2008 35(1):65-73.

10.  Yan, C., Hu, J. and Wang, Y. Discrimination of outer membrane proteins with improved performance. BMC Bioinformatics 2008, 9:47.

11.  Yan, C., Wu, F., Jernigan, R.L., Dobbs, D., and Honavar V. Characterization of protein-protein interfaces. The Protein Journal 2008 27(1):59-70.

12.  Hu, J., and Yan, C. An improved method for alpha-helical transmembrane protein topology prediction. Bioinformatics and Biology Insights 2008 2: 67-74.

13.  Hu, J., and Yan, C. Protein subcellular localisation prediction with improved performance. Int. J. Functioinal Informatics and Personalised Medicine 2008 1(3): 321-328.

14.  Yan, C., Terribilini, M., Wu, F., Jernigan, R.L., Dobbs, D., and Honavar V. Predicting DNA-binding sites of proteins from amino acid sequence. BMC Bioinformatics, 2006, 7:262.

15.  Terribilini, M. Lee, J.-H., Yan, C., Jernigan, R., Honavar, V., and Dobbs, D. Computational prediction of RNA-binding sites in proteins based on amino acid sequence, RNA, 2006, 12 (8): 1450-1462.

16.  Yan, C. and Hu, J. An exploration to the combining of solvent accessibility with amino acid sequence in the identification of helix-turn-helix motifs, WSEAS Transaction on Biology and Biomedicine, 2006, 6(3): 477-484.

17.  Yan, C., Burleigh, J.G. and Eulenstein, O. Identifying optimal incomplete phylogenetic data sets from sequence databases. Mol Phylogenet Evol. 2005, 35(3):528-35.

18.  Yan, C., Dobbs, D., and Honavar, V. A two-stage classifier for identification of protein-protein interface residues. Bioinformatics, 2004, 20(S1): i371-i378.

19.  Yan, C., Honavar, V., and Dobbs, D. Identification of interface residues in protease-inhibitor and antigen-antibody complexes: a support vector machine approach. Neural Computing & Applications, 2004, 13(2): 123 -129.

20.  Sen, T., Kloczkowski, A., Jernigan, R., Yan, C., Honavar, V., Ho, K., Wang, C., Ihm, Y., Cao, H., Gu, X., Dobbs, D. Prediction of protein binding sites by combining several methods. BMC Bioinformatcs, 2004, 5:205.

 

Refereed Conference Articles

1.        Hu, J. and Yan, C. Predicting DNA-binding sites by exploring the distribution of atom groups around the surface. In Proceedings of the 2011 International Conference on Bioinformatics & Computational Biology (BIOCOMP'11).  July 18-21, 2011, Las Vegas, Nevada, USA.

2.    Alvarez, M. and Yan, C. Exploring structural modeling of proteins for kernel-based enzyme discrimination. In Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Bioengineering. 2010, May 2-5, Montreal, Canada.

3.    Yan, C. and Luo, J. A comparison between transmembrane helices and reentrant loops. In Proceedings of IEEE International Symposium on BioInformatics and BioEngineering. 2010, May 31-June 3, Philadelphia, PA, USA.

1.      Hu, J. and Yan, C. Mining sequence features for DNA-binding site prediction. In Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Bioengineering. Sept 15-17, 2008, 219–222.

2.      Hu, J. and Yan, C. Predicting protein subcellular localizations using weighted Euclidian distance. In Proceedings of IEEE 7th International Symposium on BioInformatics and BioEngineering, 2007, 1370-1373.

3.      Shan, J., Wang, Y. and Yan, C. Toward the recognition code of protein-DNA recognition. In Proceedings of IEEE 7th International Symposium on BioInformatics and BioEngineering, 2007, 1290 - 1293.

4.      Shan, J., Ju, W. Yan, C., and Cheng, H.D. Discrimination of disease-related non-synonymous single nucleotide polymorphism using fuzzy support vector machine. In Proceedings of the 10th Joint Conference on Information Sciences, 2007, 861-867.

5.      Ju, W., Shan, J. Yan, C., and Cheng, H.D. Discrimination of outer membrane proteins using fuzzy support vector machines. In Proceedings of the 10th Joint Conference on Information Sciences, 2007, 854-860.

6.      Yan, C. and Hu, J. Identification of Helix-Turn-Helix motifs from amino acid sequence. In Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006, 2006, 1-7.

7.      Yan, C. and Hu, J. A Hidden Markov Model for the Identification of Helix-Turn-Helix Motifs. In Proceedings of WSEAS International Conference on Cellular and Molecular Biology-Biophysics and Bioengineering, 2006,14-19.

8.      Yan, C. A hidden Markov model approach to model protein sequence and structural information: Identification of helix-turn-helix DNA-binding motif. In Proceedings of IEEE International Conference on Granular Computing, 2006, 385-388.

9.      Terribilini, M., Lee, J., Yan, C., Jernigan, R.L., Carpenter, S., Honavar, V., and Dobbs, D. Identifying Interaction Sites In "Recalcitrant" Proteins: Predicted protein and RNA binding sites in Rev ProteinS of HIV-1 and EIAV agree with experimental data. In Proceedings of Pacific Symposium on Biocomputing, 2006, 11:415-426.

10.  Yan, C., Dobbs, D., and Honavar, V. Identification of surface residues in protein-protein interaction - a support vector machine approach. In Proceedings of Intelligent Systems Design and Application, 2003, 53-62.

 

Book Chapters

1.      Alvarez, M. and Yan, C. GO-Based Term Semantic Similarity.  IN Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances. Editors: Wong, W., Liu, W. and Bennamoun, M. Publisher: IGI-Global, Pennsylvania, USA. 2011. (http://www.igi-global.com/bookstore/TitleDetails.aspx?TitleId=47443). ISBN: 978-16-096-0625-1, pages 174-185.

2.      Yan, C.  Computational methods for the identification of DNA-binding sites. IN Computational and Systems Biology Methods and Applications. Editors: Mazzarella R. and Head, R. 2009. ISBN: 978-81-308-0298-5, pages 1-12.