Topics in Computational Biology:
SYSTEMS BIOLOGY
Lecturer:
Professor B.
Mishra
Time, place & lectures:
monday July 8, 2002 | 11am - 1pm [Lecture 1] |
tuesday July 9, 2002 | 2pm - 4pm [Lecture 2] |
wednesday July 10, 2002 | 11am - 1pm [Lecture 3] |
thursday July 11, 2002 | 11am - 1pm [Lecture 4] |
friday July 12, 2002 | 11am - 1pm (Cancelled) |
aula multimediale, Dipartimento di
Matematica
e Informatica, University of Udine.
Text(s):
Computational Analysis of
Biochemical
Systems : A Practical Guide for Biochemists and Molecular
Biologists
Receptors : Models for Binding,
Trafficking,
and Signaling
Course Description:
Presently, there is no clear way to determine if the current body
of
biological facts is sufficient to explain phenomenology. In the
biological
community, it is not uncommon to assume certain biological problems to
have achieved a cognitive finality without rigorous justification. In
these
particular cases, rigorous mathematical models with automated tools
for
reasoning, simulation, and computation can be of enormous help to
uncover
cognitive flaws, qualitative simplification or overly generalized
assumptions.
Some ideal candidates for such study would include: prion hypothesis,
cell
cycle machinery (DNA replication and repair, chromosome segregation,
cell-cycle
period control, spindle pole duplication, etc.), muscle contractility,
processes involved in cancer (cell cycle regulation, angiogenesis, DNA
repair, apoptosis, cellular senescence, tissue space modeling enzymes,
etc.), signal transduction pathways, circadian rhythms (especially the
effect of small molecular concentration on its robustness), and many
others.
We believe that the difficulty of biological modeling will become
acute
as biologists prepare to understand even more complex systems.
Fortunately, in the past, similar issues had been faced by other
disciplines:
for instance, design of complex microprocessors involving many
millions
of transistors, building and controlling a configurable robots
involving
very high degree-of-freedom actuators, implementing hybrid controllers
for high-way traffic or air-traffic, or even reasoning about data
traffic
on a computer network. The approaches developed by control theorists
analyzing
stability of a system with feedback, physicists studying asymptotic
properties
of dynamical systems, computer scientists reasoning about a discrete
or
hybrid (combining discrete events with continuous events) reactive
systems---all
have tried to address some aspects of the same problem in a very
concrete
manner. We believe that biological processes could be studied in a
similar
manner, once the appropriate tools are made available.
The goal of this course is to understand, design and create a
large-scale
computational system centered on the biology of individual cells,
population
of cells, intra-cellular processes, and realistic simulation and
visualization
of these processes at multiple spatio-temporal scales. Such a
reasoning
system, in the hands of a working biologist, can then be used to gain
insight
into the underlying biology, design refutable biological experiments,
and
ultimately, discover intervention schemes to suitably modify the
biological
processes for therapeutic purposes. The course will focus primarily on
two biological processes: genome-evolution and cell-to-cell
communication.
________________________________________
Bud Mishra
_________________________________________
Loc. Rizzi, via delle Scienze 206,
33100
Udine. Italy.
by Eberhard O. Voit Cambridge Univ
Pr;
ISBN: 0521785790.
by Douglas A. Lauffenburger, Jennifer
J. Linderman Oxford University Press; ISBN: 0195106636.
http://cs.nyu.edu/faculty/mishra/
http://bioinformatics.cat.nyu.edu/