These are actually not themselves the talks, but rather portions of
talks broken out into manageable segments. The presentation and presentation
source should be available.
| Topic |
View |
Description |
| Overview |
[PPT]
[Flash] |
An overview of the philosophy behind integration of
systems biology, engineering and post-genomic data sets. |
| Biological Networks: Device Physics 1 |
[PPT]
[Flash]
|
Why quantitative biology is necessary. Description
of simple bistabilities in signal transduction. |
|
Biological Networks:
Device Physics 2
|
[PPT]
[Flash] |
Stationary state vs. time dependent function.
Frequency filtering by biochemical systems. |
|
Biological Networks:
Device Physics 3
|
[PPT]
[Flash1]
[Flash2]
|
Low numbers of molecules and molecular
machines. Stochastic chemistry in biological control. Stochastic
gene expression. |
| Examples of Biosystems Analysis 1 |
[PPT]
[Flash] |
Glycolysis and computational functions
in biochemical reaction networks |
| Examples of Biosystems Analysis 2 |
[PPT]
[Flash] |
Phage lambda developmental decisions and
stochastic kinetics. |
|
Examples of Biosystems Analysis 3
|
[PPT]
[Flash] |
Control of type-1 pili phase variation
in Escherichia coli |
| Bio/Spice, a software foundation for simulation
of cellular systems |
[PPT]
[Flash] |
Preliminary discussions on the design
and implementation of the databases, kernels, and user interfaces
for the Bio/Spice tools |
| Network deduction |
[PPT]
[Flash] |
Reverse engineering of regulatory networks
from perturbation response studies |
| Reliability in biochemical systems |
[PPT]
[Flash] |
The role of redundancy and feedback in
making reliable biological systems. |
| Physical chemical challenges in Biology |
[PPT]
[Flash] |
Historical and possible future roles of
physical chemistry in biology. |
| Computational challenges in biocomputing |
[PPT]
[Flash] |
Possible roles for supercomputation and
advanced algorithms in computational systems biology |
|
Planning for the Microbial Cell project
|
[PPT]
[Flash] |
Some notes on what sorts of things should be considered when
putting together large programs in quantitative microbiology.
|
