Colloquium Series Schedule

The Department of Computer Science Colloquium Series is generally scheduled for 3:45 p.m. - 5:00 p.m. on Wednesdays or Fridays, in the Math & Computer Science Building, Room 228. Directions to our building are available.

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Colloquium for Friday, March 6, 2009
  Speaker: Dr. Joe Song, Department of Computer Science, New Mexico State University, Las Cruces, NM

  Title: Computational Modeling of Gene Regulatory Networks using Temporal Gene Expression Data

  Abstract: Modeling dynamical interactions among genes and environment can lead to a quantitative understanding of mechanisms in cellular processes, such as transcription regulation, metabolism, and disease pathways. The computational problem of identifying network models to account for temporal dependencies among interacting genes and environmental stimuli from high-throughput gene expression data is addressed. The linear discrete dynamical system model was reconstructed for a gene regulatory network in response to 5-hydroxymethylfurfural, a bioethanol conversion inhibitor for ethanologenic yeast Saccharomyces cerevisiae. A linear discrete dynamical system model consists of a system of difference equations for each variable. The statistically significant discrete dynamical system model of the yeast gene regulatory network derived from time course gene expression measurements by exposure to 5-hydroxymethylfurfural, revealed several verified transcriptional regulation events. These events implicate several transcription factors consistently known for their regulatory roles by other studies or predicted by independent sequence motif analysis, suggesting their involvement in detoxification of the inhibitor by yeast. Data pre-processing, model reconstruction, and post-processing in discrete dynamical system modeling will be discussed, which is applicable to other molecular interactions mechanisms involved in stress tolerance in biomass conversion.

Short Biography: Joe Song received his Ph.D. in 2002 and M.S. in Electrical Engineering in 1999, both from the University of Washington, Seattle. He obtained his B.S. in Electrical Engineering from Beijing University of Posts and Telecommunications in 1992. He has been an Assistant Professor at the Department of Computer Science, New Mexico State University since 2005. He was Assistant Professor of Computer Science with Queens College and the doctoral faculty with Graduate Center, City University of New York from 2002 to 2005. His research areas include statistical computing, quantitative biology, and computer vision. His research has been supported by NSF, NIH, USDA, and Los Alamos National Lab. He has received Interdisciplinary Research Grant, Graduate Research Enhancement Grant, and Undergraduate Research Initiative Grant from New Mexico State University Office of the Vice President for Research. His current research projects in systems biology involve computational modeling of large dynamic biological networks at the molecular level. His lab currently has two postdoc researchers, two doctoral graduate students, and two Master’s students. He has collaborated with life scientists on campus and around the nation to solve computational modeling problems involved in biofuels, cancer, neuroscience, and microbial communities. His research partners include scientists at Fred Hutchinson Cancer Research Center, USDA, and Lawrence Berkeley National Lab.

http://www.cs.nmsu.edu/~joemsong/

Host: Ruoming Jin

  Time: Friday, March 6, 2009, 3:45 - 5:00 PM

  Place: MSB, Room 228


Other Colloquia Scheduled for Spring 2009
  • Wednesday April 1, 2009
    Computational Thinking
    Dr. Jeannette M. Wing, President's Professor of Computer Science, Carnegie Mellon University, Pittsburgh, PA
    Assistant Director, CISE Directorate, National Science Foundation
    3:45 - 5:00 PM MSB, Room 228
  • Wednesday April 15, 2009
    Graph sandwich problems
    Dr. R. Sritharan, The University of Dayton, Dayton, Ohio
    3:45 - 5:00 PM MSB, Room 228

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Dr. L. Gwenn Volkert
Dr. Volkert directs the BioCompting and Machine Learning Research Lab, where students develop machine learning approaches to a variety of problem. Her group is especially interested in problems dealing with the large amounts of data encountered in the life sciences - including Bioinformatics, Bioengineering, and Geo-Informatics. >> more