Re: Math for Memes

From: Wade T.Smith (
Date: Sat Feb 16 2002 - 20:53:31 GMT

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    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 --
    > --

     From their 'about' section- looks interesting.

    - Wade


    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
    other agreements.

    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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