The second half of the last century produced a staggering wealth of information about the cellular and molecular processes of life. The quantity and quality of this data is ushering in a new mode of thinking in the biomedical sciences that relies heavily on mathematical and computational tools and on rigorous quantitative experimental methods. With increasing frequency, the analytical tools and experimental methods are not home grown within the life sciences, but are adopted from research in the physical sciences. This brave new world requires a new kind of researcher, one who easily moves between the bench and the workstation, one who is equally at ease with running microscopes as with running simulations, and one for whom building quantitative models and testing them by designing equally quantitative experiments comes naturally. The Quantitative Biology (QB) Program at Brandeis University brings together six different Ph.D. programs from four science departments in order to train students who can rise to this interdisciplinary challenge. QB is an official interdepartmental graduate program at Brandeis that has just completed its second full academic year of operation;the program currently has 21 enrolled students. QB leverages the strengths of existing disciplinary Ph.D. programs at Brandeis by bringing together students from these programs in a specialized curriculum that is designed to take advantage of the learning opportunities afforded by training in multi-disciplinary groups. Students admitted to graduate study in the Biochemistry, Biophysics &Structural Biology, Chemistry, Molecular &Cellular Biology, Neuroscience, or Physics Ph.D. programs and who choose the QB track will, upon successful completion, receive a Ph.D. degree in their chosen discipline """"""""with an additional specialization in Quantitative Biology"""""""". This approach provides the students with modern discipline-bridging training while providing the graduate with a Ph.D. credential that has proven value on the job market because it is in a recognized traditional discipline. Students typically enter the QB program in either the first or second years of their Ph.D. studies and remain affiliated with QB until they graduate. Each student selected for support by the training grant will be supported during years 2 and 3 of their studies.

Public Health Relevance

The goal of the Quantitative Biology program is to train Ph.D. scientists who are well equipped to bring quantitative experimental, computational, and mathematical methods from Physics and Chemistry to bear on important problems in biomedical research. It is anticipated that the work of these scientists will lead to improvements in public health by advancing basic research in directions that are not readily accessible to scientists who lack interdisciplinary training.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Institutional National Research Service Award (T32)
Project #
5T32EB009419-02
Application #
7797603
Study Section
Special Emphasis Panel (ZEB1-OSR-E (J1))
Program Officer
Erim, Zeynep
Project Start
2009-07-01
Project End
2014-06-30
Budget Start
2010-07-01
Budget End
2011-06-30
Support Year
2
Fiscal Year
2010
Total Cost
$266,942
Indirect Cost
Name
Brandeis University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
616845814
City
Waltham
State
MA
Country
United States
Zip Code
02454
Herzog, Josiah J; Deshpande, Mugdha; Shapiro, Leah et al. (2017) TDP-43 misexpression causes defects in dendritic growth. Sci Rep 7:15656
Mohapatra, Lishibanya; Lagny, Thibaut J; Harbage, David et al. (2017) The Limiting-Pool Mechanism Fails to Control the Size of Multiple Organelles. Cell Syst 4:559-567.e14
Halpin, Jackson C; Street, Timothy O (2017) Hsp90 Sensitivity to ADP Reveals Hidden Regulation Mechanisms. J Mol Biol 429:2918-2930
Tetone, Larry E; Friedman, Larry J; Osborne, Melisa L et al. (2017) Dynamics of GreB-RNA polymerase interaction allow a proofreading accessory protein to patrol for transcription complexes needing rescue. Proc Natl Acad Sci U S A 114:E1081-E1090
Tompkins, Nathan; Fraden, Seth (2016) An inexpensive programmable illumination microscope with active feedback. Am J Phys 84:150-158
Wang, A L; Gold, J M; Tompkins, N et al. (2016) Configurable NOR gate arrays from Belousov-Zhabotinsky micro-droplets. Eur Phys J Spec Top 225:211-227
Halpin, Jackson C; Huang, Bin; Sun, Ming et al. (2016) Crowding Activates Heat Shock Protein 90. J Biol Chem 291:6447-55
Harbage, David; Kondev, Jané (2016) Exact Length Distribution of Filamentous Structures Assembled from a Finite Pool of Subunits. J Phys Chem B 120:6225-30
Perkett, Matthew R; Mirijanian, Dina T; Hagan, Michael F (2016) The allosteric switching mechanism in bacteriophage MS2. J Chem Phys 145:035101
Vimal, Vivekanand Pandey; Lackner, James R; DiZio, Paul (2016) Learning dynamic control of body roll orientation. Exp Brain Res 234:483-92

Showing the most recent 10 out of 44 publications