Re: The Simpson-Elsasser-Wolfram framework for modeling the cell val wrote (>):

>>  The method employed by physicists in modeling the atom was essentially
>> based on mathematics without relying on the computer, but the method
>> that biologists will need to model the cell may turn out to be, not
>> mathematics, but mainly logic- and computer-based. The purpose of this
>> post is to discuss the theoretical rationale underlying this admittedly
>> audacious proposition.  My thinking along this line has been greatly
>> influenced by the ideas and concepts advocated by the following three
>> scientists -- the American paleontoligist G. Simpson (1902-1984), the
>> German-American physicist-turned biolgist W. Elsasser (1904-1991),
>> and the British-American physicist-turned computer scientist S. Wolfram
>> (1959-  ).
>>  Their ideas relevant to the presnt post are briefly summarized below:
>>
>> 1)  G. Simpson:
>>     Physicists study the principles that apply to all phenomena:
>>     Biologists study phenomena to which all principles apply.
>
> i'm not sure there is any in-depth content behind that statement - which
> "all principles" get applied to phenomena in biology?

Table 1.  A partial list of the principles, laws and concepts that is
          deemed essential in understanding the phenomenon of life.
__________________________________________________________________________

Field                       Principles, Laws & Concepts
__________________________________________________________________________

1. Physics:
   relativity               curved spacetime (leading to the metabolic
                            spacetime of H. A. Smith and G. R. Welch; see
                            pp. 282-323 in "Molcular Theories of Cell Life
                            and Death", S. Ji, ed., Rutgers University
                            Press, New Brunswick, 1991)

   thermodynamics           energy, entropy

   statistical mechanics    Brownian motions, microstates
                            Gibbs free energy

   quantum mechanics        electronic transitions, bond vibrations &
                            bending, Bohrian complementarity, nonlocality

   nonlinear dynamnics      deterministic chaos, fractals,
                            attractors, sensitive dependence on
                            initial conditions

2. Chemistry:
   molecular structures     duality of covalent and noncovalent
                            molecular interactions, conformation changes,
                            H-bonding, structural complementarity

  chemical kinetics         duality of kinetic and equilibrium controls,
                            transition states, absolute rate theory,
                            rate laws, rate constants, concentrations,
                            activity

3. Biology:                 evolution (variation, interaction & seletion),
                            genes, inheritance, tree of life

4. Cybernetics:             law of requisite variety, feed back loops
                            (positive & negative), machines, information

5. Computer science:        principle of computational equivalence,
                            recursion, programs, algorithms, computer
                            architecture, celluar automata, massive
                            parallel computing, analog vs. digital
                            computing

6. Mathematics:             mathematics of continuous vs. discrete
                            processes, probability, differential and
                            integral equaitons, combinatorics

7. Logic:                   triadic logic of Peirce

8. Linguistics:             rule-governed creativity, double articulations,
                            synchronicity vs. diachronicity, syntagmatic
                            vs. paradigmatic relations

9. Metaphysics:             Peircean categories of Firstness, Secondness
                            and Thirdness, semiotics, signs, interpretants,
                            objects, the universality of logic in both
                            biotic and abiotic worlds (which may be deeply
                            connected with Wolfram's principle of
                            computational equivalence)

___________________________________________________________________________


>> 2)  W. Elsasser:
>>     Physicists study objects that belong to pure classes to which
>>     mathematical methods can be applied; bilogists study objects that
>>     belong to heterogenous classeses to which logic, but not
>>     mathematics, can be applied.
>
> well, logic is certainly a part of math;

I would say the other way around: Math is a part of logic.

> what i see here is that
> phenomena in biology are unique ("heterogeneous"), and traditional
> generalizations in physics such as mass, velocity, momenta, energy,
> rotational momenta, trajctories, etc obviously have little to do with
> biological reality

   These all have roles to play in biology, both at the macroscopic and
microscopic levels, which would fit the Sympsonian thesis described
above.

>and thus biology needs *application-specific* logic
> directly related to the specific observations; though, a certain degree
> of generalization takes place in biology as well - differentiation,
> growth patterns, adaptation to the local env, patterns of behavior,
> generational continuity of living matter, etc
>  >
>  > 3)  S. Wolfram:
>  >     All structures and phenomena, whether internal or external,
>  >     can be modeled on the computer as fractals, namely, the
>  >     structures and patterns that emerge as the consequences of
>  >     iterating the application of sets of simple rules n times, where
>  >     n can be a large number (10-1000?).
>  >
>  > With all the best.
>  > Sung
>
> Hmm.. All structures and phenomena? as fractals? as the consequence of
> repeated application of simple rules?..

If not all as fractals, just as simple programs involving repeated
application of select rules, leading to all kinds of structres an
dprocesses, including fractals on occasion.

>And where are the captured
> cause-effect dependencies typical for real world - such as the applied
> forces and trajectories (mechanics), or moving charges and fields
> (electrodynamics), or particles-waves (quantum mechanics)?

As I understand it, these are all the results of applying continuous
mathematics to physcial processes.  As such they must apply to living
processes as necessary components (accoriding to the Simpson doctrine) but
are not sufficient to account for life (according to Elsassser).

> And how
> "simple rules" repeated zillion times can reproduce hydrogen atom and
> its dynamics?  Never..  That would be the seventh wonder of the world..

This may be possible if we can transform quantum mechanical formalisms
into algorithmic ones using finite sets of if-then rules. This is how I
understand Wolfram's principle of computaitonal equivalence.

>
>        Yet, your point about importance of *direct, computer-driven*
> methods of analysis of cell dynamics sounds right to me.  I'm going to
> comment on that in my next post..

Sung

