Biology, technology and information

Information Technological Biology/Biological Information Technology

Ray Paton

The two-way displacement of ideas between the biosciences
and engineering/technology has a long history. In this century
we have seen many developments - too many to list. However,
lets briefly pursue one:

what is a brain - a telephone exchange, a computer
what is a neuron - a switch, a microprocessor, the multiplex neuron,
                      a computer

Here we have some mechano-electrical ideas.

Another would be that the brain is a gland
    or memory is hologram etc.

So it should come as no surprise that in looking for more
general ideas are displaced from technology.

   Nature gets writ in technological terms.

Technology can also be writ in natural terms. DNA 'computing'
was around a long time before Adleman. However, you didn't need a
Turing machine to understand or argue about it.

The purpose of this short contribution to the FIS discussion
is to consider the scope and limitations of this two-way
exchange SPECIFICALLY in relation to our understanding
of Biological Information Processing Systems.

When we ask the question about whether bioinformation
is (should be) corpuscular or abstract object or process
or some'thing' like energy or part of an equation.
Maybe the parallel with phlogiston is 'phlogging a dead horse'.
Rather, the construct we are looking for could have more
to do with the debates/discussions that gave
rise to the notion of energy in the nineteenth century.
There again, information is maybe a third category
as Werner and others have argued.

Getting beyond the Syntax - The Notion of 'Smart'
------------------------------------------------
One of the problems I feel that underpins this debate
about bioinformation is concerned with meaning which in
turn often gets conflated either with syntax and linguistics
or sign and semiotics. To be sure these are valuable
ideas but so too is the cognitive dimension [as espoused by
various authors such as Kampis, Erdi, Varela etc etc ...]

'Smart' is used to describe a number of engineering materials
and it should come as no surprise that proteins and maybe to a lesser
extent DNA fall into this category. When discussing the idea of smartness
we look around for some valuable sources. These might include:

  - - parallel distributed processing
  - - cognitive agents
  - - emergent computation

Consider some examples of proteins which exhibit 'smartness'.
Kinases and phosphatases would fall into this category.
Also, we could suggest that a transcription complex is particularly
smart or proteins involved in DNA methylation with relation to
imprinting and epigenetic inheritance systems - - in my view
that is definitely when smary/clever etc become useful adjectives.
The context-sensitivity and multifunctionality showed by
say CaM Kinase II illustrates the point about enzyme action.
Michael Conrad has talked about a seed-germination model
because of the complex of factors that can be involved. Dennis Bray
has drawn parallels with PDP networks and Pedro,
Rick Welch and others make use of society ideas. We have also looked
at a number of computational analogues namely:

   * Enzymes as 'Logical' Agents (using ideas from emergent
        and distributed AI) such as autonomous and adaptive agents.

   * Enzyme as Verb (to emphasise the process, network and
        spatio-temporal aspects)

You could say that some genes are 'smarter' than others for example,
the genes coding for regulatory proteins in prokaryotic hirearchies
such as regulons and modulons.

Think BioProcess - Think Micro[meso] process
--------------------------------------------
The metaphor of cell as a chemical lab etc is OK so long as
even the reaction vessels are viewed as highly organised. This focusses
attention on small scale thinking rather than bulk processes
in big vats. This affects our thinking about

What is a genome ?
IS it just a bag of genes - - NO.
And a metabolism is not a bag of enzymes.

Structure and spatial heterogeneity play a key role.
This related to micro-compartmentation and also to the roles
of the internal skeleton. Maybe an intersting parallel here
is that just as macro skeletons play multifunctional roles
so do cyto and nuclear skeletons. Eslewhere, I describe this apsect
of bioinformation as the 'stage'.
Put another way, information=form [Thom].

Some eukaryotic genomes have more than 95% non-protein coding DNA.
If you were thinking of chemical lab/factory ideas
then you might say your system is only 5% efficient.
But info is NOT just about a code. Indeed, there are several codes.
Maybe emphasis on 'code' prevents a richer understanding anyway.

How important is structural information?
What about the roles of mobile genetic elements?
What does this say about biological information - it is dynamic.
Fluid genomes require a wider number of information processing
ideas [see eg Shapiro, Thaler, etc...]. Hierarchical thinking
in many ways requires information as GLUE.

Think Smart - Think Ecology
----------------------------
The [so-called] code-script of Schrodinger is
NOT JUST Harware AND software AND data. An ecological
perspective on the interactions between the script,
the actors and the stage is needed.

To return to the issue of engineering/technology and biology,
Jim Shapiro asks whether evolution is more about [natural]
genetic engineering than the workings of a blind watchmaker.
If biocience has anything in common with information technology
this seems a very interesting question to ask.

Ecological thinking brings us back to semiotic, thermodynamic
and spatiotemporal issues.

     "All true biologists desrve the coveted name of naturalist.
      The touchstone of the naturalist is his abiding interest in
      LIVING Nature in all its aspects"
                                Frederick Gowland Hopkins (1936)

SO in any replies please give some specific examples.

HOW CAN ALL THESE IDEAS BE INTEGRATED ???
=========================================

        BIOINFORMATION=GLUE

If anyone is interested we could explain further.
Received on Fri Mar 6 15:33:31 1998