Kirk on ID

From: NSS (kirk@newscholars.com)
Date: Wed Nov 12 2003 - 14:19:17 EST

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    Some good questions have been raised. My short answer to Wayne is that my
    method is constructed to yield no false positives. Thus it will fail to
    identify innumerable instances of ID, but it when it does indicate an
    instance of ID, you can be sure ID is required. Especially problematic will
    be instances of ID designed to 'look natural' as an election scam would try
    hard to do. In the case you suggest, one instance would almost certainly be
    undetected by my approach, although there might be a particular component of
    the scheme that might yield a positive result. My priority is to avoid false
    positives while, at the same time, identifying instances that would
    *require* ID. I will define 'require' in a later post, in the course of my
    forthcoming explanation.

    With regard to Howard's concern, I think it would be incumbent on me to show
    that his view does not represent the method I propose.

    Walt's question is central to the discussion of computer simulations and the
    generation of functional information.

    The only way I can see myself proceeding in a way that would actually
    accomplish something, is to move ahead one point at a time. I ask Walt,
    Howard, and Wayne to have patience as I try to see if we can establish some
    generally agreed-to foundations. Eventually, all their questions will be
    addressed.

    It will help me if I can use html text in my emails. Will this be a problem
    for anyone? I'll refrain from doing so until I'm given the go-ahead.

    START:

    To begin, the Shannon approach to quantifying information does not generally
    distinguish between functional (or meaningful) information and
    non-functional, or meaningless, information. Thus the term 'information' is
    taken in its broadest sense possible, under Shannon information. Jack
    Szostak has raised this problem in his recent article ('Molecular messages',
    *Nature* Vol. 423, (2003), p. 689.) He doesn't go into a great amount of
    detail, but the bottom line is that functional information can be defined,
    in units of bits, as:

    If = -log2(Nf/N) (1)

    where Nf = number of states/sequences/configurations that are functional
    and, N= total number of possible states/sequences/configurations that are
    possible for the physical system under investigation.

    'Functional' can be taken generally or specifically. Generally, 'functional'
    means that the state/sequence/configuration has some
    positive/meaningful/useful effect within a larger system. Within the large
    category of 'functional' will be any number of specific functions. Within
    genetics we are usually concerned with the specific function(s) of a given
    protein or regulatory sequence.

    Eqn. (1) also assumes that each possible state/sequence/configuration is
    approximately as probable as any other.

    Are we okay with using Eqn. (1) as my method to quantify functional
    information? If not, what might be your objection. Are there any questions
    about Eqn. (1) before I proceed? If someone wants the derivation, I can
    provide that (email me off list and I will send you a properly formatted
    derivation).

    Since Eqn. (1) is essential for any further progress, I will stop here. I am
    not a member of this list, so will not see your comments unless you email me
    directly, or Denyse forwards your post to me. I have more emails/day than I
    can handle already, so I cannot afford to receive the additional emails/day
    that being a member of the ASA list would produce. Thus this compromise.

    Cheers,

    Kirk



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