Computational Bioinformatics & Bio-imaging Laboratory (CBIL)


 
 

Internal Use

large size photo

 

By striving for scientific discoveries and pursuing engineering innovations for the molecular analysis of human diseases, our interdisciplinary research work follows the roadmap of three evolving yet integrative strategies: (1) Identify and validate predictive molecular markers via comprehensive characterization of genomic expression patterns (SNPs, gene expressions, proteomics); (2) Hypothesize and elucidate mechanistic molecular markers and their interactions via computational modeling, dissection, and reconstruction of pathway signaling and gene regulatory networks; and (3) Visualize the in-vivo functions of mechanistic molecular markers via multichannel cellular and molecular imaging of biological processes.

Our primary research interests are twofold. In pursuing engineering innovations, we study computational intelligence, pattern recognition, machine learning, statistical information visualization, and advanced imaging and image analysis. In pursuing scientific discoveries, we perform molecular analysis of human diseases (cancer, muscular dystrophy, lung and heart disease, neuronal degeneration) via high-throughput molecular profiling and integrative data analysis, computational modeling and reconstruction of pathway signaling and gene regulatory networks, and multichannel molecular and cellular imaging of biological processes.

We are standing at a major inflection point for biomedical science - the way we view and practice scientific research is changing profoundly. These changes are being driven by systems biology, an interdisciplinary and data-driven approach to biomedicine, which will increasingly transform biomedicine from disease-driven and reactive to health-driven and predictive, yet preventative. Personalized molecular profiling, computational systems biology, and biomedical imaging will revolutionize our ability to generate comprehensive data sets that span from individual cells to patients, and will allow us to model and reconstruct molecular regulatory and signaling pathway networks associated with the biological processes of interest. Our research has evolved from comprehensive characterization of gene and protein expression patterns to the computational theory of systems biology, and to advanced imaging and image analysis.

 

Virginia Tech
The Bradley Department of Electrical and Computer Engineering
Virginia Tech Research Center - Arlington
900 N. Glebe Road, Room-214
Arlington, VA 22203 (Washington DC Metropolitan)

CBIL photos http://www.cbil.ece.vt.edu/images/CBIL2012.JPG http://www.cbil.ece.vt.edu/images/CBIL11.JPG http://www.cbil.ece.vt.edu/images/CBIL2010.JPG http://www.cbil.ece.vt.edu/images/CBIL09.JPG http://www.cbil.ece.vt.edu/images/CBIL08Summer.JPG http://www.cbil.ece.vt.edu/images/CBIL07.JPG http://www.cbil.ece.vt.edu/images/CBIL06.JPG

Graduate Research Assistantships http://www.cbil.ece.vt.edu/GRAOpenings.pdf

We are electrical and computer engineering researchers by training who have developed a great interest in multiscale, computational, integrative, and systems biomedical sciences, mainly inspired by our curiosity about the process of discovery. We enjoy close collaborations with biologists and physicians, and these partnerships provide us with the opportunities to learn new things, to ask new questions, and to pursue new discoveries. Our major research partners include Georgetown University Medical Center, Children's National Medical Center, Johns Hopkins Medical Institutions, National Institutes of Health, Food and Drug Administration, and Howard Hughes Janelia Farm Campus.

We are developing a research and educational program of excellence in computational bioinformatics and bio-imaging, with an emphasis on the strategic frontier between computational intelligence and the biomedical sciences and on the truly interdisciplinary nature of educating future scientists and engineers.



Copyright ©2004, Computational Bioinformatics and Bioimaging Laboratory (CBIL), Virginia Tech. CBIL is a participant of caBIG (http://cabig.nci.nih.gov), honored with the Computerworld 21st Century Achievement Award in the Science category.

Last Updated: 02/17/2009. Suggestions/Comments - Webmaster