Structural Biology and Molecular Applications Branch (SBMAB)
     
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SBMAB Staff

Couch, Jennifer, Ph.D.Chief
Knowlton, Randy, Ph.D.Program Director
Li, Jerry, Ph.D.Program Director
Brown, Robin, M.S.Program Associate Director
Lee, DianaExtramural Support Assistant

The Structural Biology and Molecular Applications Branch (SBMAB) supports cancer research and discovery in three broad areas: technology development and molecular applications, biophysical biology, and computational/mathematical methods and bioinformatics development. The branch also supports integrated and systems biology approaches to cancer biology, employing high throughput technologies, information science, and computational modeling. Research interests include biophysics, synthetic biology, molecular interactions genomics, proteomics, metabolomics, epigenomics, nanotechnology, molecular and cellular imaging, combinatorial chemistry, bioinformatics, computational and mathematical modeling, theoretical approaches to cancer biology, and the development of the technologies and software that enable this research.

Program Areas

Biophysics and Structural Biology

The program area supports research on the determination of macromolecular crystal structures; biophysical characterization of molecules and complexes; and computational structure prediction.

Computational Biology and Bioinformatics

The program area supports research on single scale computational models of cancer processes; multi-scale computational models of cancer processes; and computer aided data analysis, integration, and visualization.

Bioengineering and Technology Development

The program area supports research on instrumentation, biosensors, nanotechnology, and hardware; protein-based technologies; cell mechanics and other physical measures; genomic, epigenomic, and gene expression, metabolomic and proteomic technologies; technologies for molecules other than nucleic acids and proteins, as well as synthetic biology..

System Biology

The program area supports research on new quantitative methodologies and/or high throughput biology; integrated computational and experimental biology studies; and collaborations with Integrative Cancer Biology Program.