Yun Zhang Ph.D. Candidate Research Advisor: Dr. Michael A. Langston Department of Computer Science The University of Tennessee Mailing Address: 203 Claxton Complex, Knoxville, TN 37996-3450 Email: yzhang AT cs.utk.edu Office: Claxton 347 Phone: (865) 974-0516 Fax: (865) 974-4404 This page: http://www.cs.utk.edu/~yzhang

Biography

• Research Assistant for Biosciences Division at ORNL, from Fall 2006.
• Graduate Research Assistant Award, U. of Tennessee, Summer 2006.
• Research Assistant for Computer Science and Mathematics Division at Oak Ridge National Laboratory, Fall 2004 ~ Spring 2006.
• Teaching Assistant, Spring 2004, CS100.

Research Interests

• High Performance Computing for Large-Scale Graph Algorithms
• Graph Theory
• Computational Biology, BioInformatics

Current Research Projects

• Fast Maximal Biclique Enumeration Algorithms for Biological Bipartite Graphs
• Combinatorial Analysis of Linkage Disequilibrium
• Fast Maximal Clique Enumeration Algorithms for Gene Expression Analysis and Polymorphism Analysis.
• Fast Maximum Common Subgraph Algorithms for Protein Classification

Publications

• W. H. Suters, F. N. Abu-Khzam, Y. Zhang, C. T. Symons, N. F. Samatova, and M. A. Langston. A New Approach and Faster Exact Methods for Maximum Common Subgraph Problem. Proc. of International Computing and Combinatorics Conference, Kunming, China, August 2005.
• Y. Zhang, F. N. Abu-Khzam, N. E. Baldwin, E. J. Chesler, N. F. Samatova, and M. A. Langston. Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology. Proc. of SC2005, Seattle, Washington, November 2005.
• F. Dehne, M. A. Langston, X. Luo, S. Pitre, P. Shaw and Y. Zhang. The Cluster Editing Problem: Implementations and Experiments. Proc. of International Workshop on Parameterized and Exact Computation, Zürich, Switzerland, September, 2006.
• Y. Zhang, E. J. Chesler, and M. A. Langston. On Finding Bicliques in Bipartite Graphs: a Novel Algorithm with Application to the Integration of Diverse Biological Data Types. Accepted by HICSS-41, Big Island, Hawaii, January, 2008.

Posters

• Y. Zhang, R. Kirova, G. Churchill, M. A. Langston, and E. J. Chesler. Comparison of Genetic Structure of Mouse Population by Combinatorial Analysis of High-Order Long-Range Linkage Disequilibrium Networks Using High Density Genotypes. UT-ORNL-KBRIN Bioinformatic Summit, April 13-15, 2007.

Recent Talks

• Scalable Graph-Theoretical Approaches to Biological Network Analysis, SIAM Conference on Parallel Processing for Scientific Computing, SIAM-PP06, San Francisco, February 22-24, 2006.

Courses

• CS594 Fixed-Parameter Tractability, Fall 2006.
• CS594 Data Mining Practices and Principles, Spring 2006.
• CS680 Graph Theory, Fall 2005.
• CS594 Understanding Parallel Computing, Spring 2005.
• CS581 Advanced Design and Analysis of Algorithms, Spring 2005.
• CS530 Computer Systems Organization, Fall 2004.
• CS560 Operating Systems, Spring 2004.

Useful Links

• A Science Primer for Bioinformatics, by National Center for Biotechnology Information.
  A basic introduction to several bioinformatics topics (e.g. Microarray technology, SNPs) using computer scientists understandable language. Applications of those biotechnologies are also provided within each topic.
  
  
• Algorithms for Gene Expression and Proteomics, Center for Bioinformatics, McGill University.
  A course website contains topics including Gene Expression, Microarray, SNPs, etc. written by students.
  
  
• Wellcome-CTC Mouse Strain SNP Genotype Set, Wellcome Trust Centre for Human Genetics.
  
  
• The Boost Graph Library (BGL). A C++ library provides various graph algorithms including BFS, DFS, Shortest Paths, etc.
  
  
• Global Arrays, Pacific Northwest National Laboratory.
  A toolkit provides an efficient and portable "shared-memory" programming interface for distributed-memory computers.