Received: by alpheratz.cpm.aca.mmu.ac.uk id UAA29140 (8.6.9/5.3[ref firstname.lastname@example.org] for cpm.aca.mmu.ac.uk from email@example.com); Sat, 16 Feb 2002 20:58:46 GMT Date: Sat, 16 Feb 2002 15:53:31 -0500 Subject: Re: Math for Memes Content-Type: text/plain; charset=US-ASCII; format=flowed From: "Wade T.Smith" <firstname.lastname@example.org> To: email@example.com Content-Transfer-Encoding: 7bit In-Reply-To: <LAW2-F62VzfzmmsiFZq00005ccf@hotmail.com> Message-Id: <3C70A3B0-231F-11D6-B12D-003065B9A95A@harvard.edu> X-Mailer: Apple Mail (2.480) Sender: firstname.lastname@example.org Precedence: bulk Reply-To: email@example.com
On Saturday, February 16, 2002, at 03:30 , Grant Callaghan wrote:
> I can't remember who it was who was looking for mathematical models
> that might be useful for the analysis of memes, but here is a paragraph
> from the home page of The Institute for System Biology --
> WWW.systemsbiology.org --
From their 'about' section- looks interesting.
Virtually all important biological phenomena, from a cell's utilization
of sugars to the functioning of the human heart, are the result of
complex systems. For decades, biologists have studied individual genes
or proteins in isolation and have made some pivotal discoveries. But
this approach has been limited by the fact that biological systems
involve many elements working together. The Institute's approach focuses
on the whole biological system by creating a detailed description of all
the parts and an analysis of their interrelationships as the biological
system performs its functions.
The Human Genome Project initiated new approaches to biology termed
discovery science. This approach focuses on gathering information; that
is, defining all the elements in a system and placing them in a database
rather than seeking to prove or disprove a particular theory. This
global information is then used to inform traditional hypothesis-driven
science by determining how all the elements in a biological system
behave when it is perturbed.
The Institute is developing and refining high-throughput facilities the
combinations of machines and instruments needed for DNA sequencing,
genotyping, DNA arrays, proteomics, cell sorting and a wide variety of
single-cell assays. The Institute's goal is to pioneer information
capture by faster and less costly high-throughput platforms that are
fully automated from sample preparation to final analysis.
The Institute's mathematicians and computer scientists are creating
powerful computational software to understand complex systems. This
requires the analysis of large data sets, the integration of many
different types of biological information, the graphical display of the
integrated data and, finally, the mathematical modeling of biological
complexity. These computational tools constitute one of the grand
challenges in biology for the 21st century.
Collaboration between specialists in biology, chemistry, computer
science, engineering, mathematics and physics is at the core of the
Institute's approach to shaping new biological research methods and
technologies. The challenge is how to educate cross-disciplinary
scientists to understand biology in a deep sense and collaborate
effectively in terms of executing systems biology.
Institute faculty members have played pioneering roles in developing new
machines for and new approaches to genomics, proteomics and high-speed
cell sorting. Technological development is a significant focus of the
Institute. Goals include developing new and refining existing
high-throughput platforms and creating better mathematics approaches for
capturing, storing and distributing biological information.
The Institute focuses considerable research on simple model organisms
(bacteria, yeast, fish, flies, sea urchins and mice). Model organisms
can be perturbed genetically, biologically or environmentally with
respect to the functioning of particular systems and the interrelations
of the component parts can then be studied. The ability to study
biological systems of model organisms provides the Rosetta stones for
understanding how these same systems function in humans.
The Institute currently has partnerships with eight private companies
including the Arctic Region Supercomputing Center at the University of
Alaska, the University of Washington, the Fred Hutchinson Cancer
Research Center, and other universities and institutes.
The Institute's structure, as an independent non-profit collaborating
with the private sector and universities, is unique and provides
significant advantages. Chief among them is a single focus--systems
biology an objective shared by the faculty and staff. In addition,
scientists from diverse disciplines are able to work at the Institute
together as teams to attack specific technology or systems problems. The
structure also provides for efficient administration and the flexibility
to move quickly to recruit top talent and to enter into partnerships or
This was distributed via the memetics list associated with the
Journal of Memetics - Evolutionary Models of Information Transmission
For information about the journal and the list (e.g. unsubscribing)
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