Transcript PDF 0.8 MB - National Centers for Systems Biology

NIGMS Center for Quantitative Biology
at Princeton
NIGMS
Lewis-Sigler Institute for Integrative Genomics
Princeton University
Research and Teaching at the Lewis-Sigler Institute
• Multi-disciplinary Faculty
-- Chemistry, Chemical Engineering, Computer Science,
Ecology and Evolutionary Biology, Molecular Biology, Physics
• Organic Connection between Research and Teaching
-- Lewis-Sigler and Theory Fellows
• Basic Research in Quantitative & System-Level Biology
--Theory <----> Experiment
--Model organisms: bacteria, yeast, worms, flies, animal cells
• Undergraduate and Graduate Curricula in Quantitative Biology
--Integrated science education for the 21st century
• High-Technology Research Infrastructure & Teaching Labs
-- NIGMS Center for Quantitative Biology
NIGMSCenter-supported Infrastructure
• Microarray/2nd Generation Sequencing Core: Wei Wang,
Ph.D. (July 1)
• Advanced Imaging Core: Stephan Thiberge, Ph.D.
• Mass Spectrometry Core: David Perlman, Ph.D.
• Computation/Bioinformatics Core: Kara Dolinski*, Ph.D. &
John Matese, Ph.D.
• * also our administrator
Co-Publications among Members of NIGMS Center since 2003 (120 of 376)
*
Outcomes: Classes of 2008 - 2010
Of a total of 51 who finished the freshman course [18 (2008) +14 (2009)
+19 (2010)], 29 ultimately received the Certificate in Quantitative Biology.
Of these 29: 11 are women
18 majored in biology, 3 in physics, 3 in chemistry, 2 in
CS, 2 in EE, 1 in CHE
21 are enrolled in graduate programs (6 Harvard, 3 MIT, 3
Stanford, 2 Berkeley, 2 Yale, U. Washington, Oxford, U. Colorado,
Columbia, Carnegie Mellon/Pitt)
2 are in industry (Microsoft, Bridgewater Associates)
2 are research assistants (Walter Reed, Harvard)
1 is teaching high school
1 is a volunteer in Africa & currently applying to Grad Programs
Enrollment in this year’s freshman class was 31: 16 (50%) women
Graduate Program in Quantitative and Computational
Biology: http://www.princeton.edu/qcbgrad
Collaborating/Alternative Graduate Programs: Chemistry, Computer
Science, Ecology & Evolutionary Biology, Neuroscience,
Molecular Biology, Physics.
Method and Logic in Quantitative Biology (I)
A graduate course, taught with Ned Wingreen, in which selfselected beginning graduate students (about equal numbers of
biologists and physicists) read closely and discuss original papers
Luria and Delbrück, 1943, Mutations of bacteria from
virus sensitivity to virus resistance
Elowitz et al., 2002, Stochastic gene expression in
a single cell
Novick A, Wiener M. 1957. Enzyme Induction as an
All-or-None Phenomenon”.
Barkai and Leibler 1997. Robustness in simple
biochemical networks”
Goldbeter and Koshland 1981.An amplified sensitivity
arising from covalent modification in biological systems”.
Hopfield JJ. 1974. Kinetic Proofreading: A New Mechanism
for Reducing Errors in Biosynthetic Processes Requiring
High Specificity
Method and Logic in Quantitative Biology (II)
Smith and Waterman 1981. Identification of
common molecular subsequences
Felsenstein 1981. Evolutionary trees from DNA
sequences: a maximum likelihood approach.
Eisen JA. 1998. A phylogenomic study of the MutS
family of proteins.
Eisen MB et al., 1998. Cluster analysis and display
of genome-wide expression patterns.
Hodgkin AL, 1958. Croonian Lecture, Ionic
movements and electrical activity in giant nerve fibres.
In the discussions, the physicists and biologists are encouraged to
explain what they understand and recognize to each other.
The course includes problems (little projects, really) that require
both some biological insight and some analysis, often a simple
simulation that can easily be done in Matlab.
The primary goal: facilitate communication across disciplinary lines
Princeton Center Presentations
• Greg Lang
• Hilary Coller
• Poster session: Eric Suh (Coller Lab)