Dear FISers and all,
I include below another response to Immanuel post (from Guenther). I
think he has penned an excellent response--my only addition is to
expostulate a doubt. Should our analysis of the human (or cellular!)
communication with the environment be related to linguistic practices?
In short, my argument is that biological self-production becomes "la
raison d'etre" of communication, both concerning its evolutionary
origins and the continuous opening towards the environment along the
different stages of the individual's life cycle. It is cogent that the
same messenger plays quite different roles in different specialized
cells --we have to disentangle in each case how the impinging "info"
affects the ongoing life cycle (the impact upon the transcriptome,
proteome, metabolome, etc.) There is no shortcut to the endless work
necessary--wet lab & in silico. So I think that Encode and other big
projects are quite useful in the continuous exploration of biological
complexity and provide us valuable conceptual stuff--but looking for
hypothetical big formalisms (I quite agree) is out sight. Molecular
recognition which is the at the fundamentals of biological organization
can only provide modest guidelines about the main informational
architectures of life... beyond that, there is too much complexity,
endless complexity to contemplate, particularly when we try to study
multicellular organization. Anyhow, this topic of the essential
informational openness of the individual's life cycle appears to me as
the Gordian knot to be cut for the advancement of our field: otherwise
we will never connect meaningfully with the endless info flows that
interconnect our societies, generated from the life cycles of
individuals and addressed to the life cycles of other individuals. Info
sources, channels for info flows, and info receptors are not mere
Shannonian overtones, they symbolically refer to the very info skeleton
of our societies; or looking dynamically it is the engine of social
history and of social complexity.
Well, sorry that I could not express myself better.
all the best--Pedro
Günther Witzany wrote:
Dear all!
What is the opposite of a linguistic description? a non-linguistic
description? Please tell me one possible explanation of a
non-linguistic description. So Im not convinced of the sense of the
term "information".
Concerning the "difference" of physical and semantic information: What
would you prefer in the case of plant communication. Does the chemical
Auxin represent a physical or a semantic information? Auxin is used in
hormonal, morphogenic, and transmitter pathways. As an
extracellular signal at the plant synapse, auxin serves to react to
light and gravity. It also serves as an extracellular messenger
substance to send electrical signals and functions as a
synchronization signal for cell division. At the intercellular,
whole plant level, it supports cell division in the cambium, and at
the tissue level, it promotes the maturation of vascular tissue during
embryonic development, organ growth as well as tropic responses and
apical dominance. In intracellular signaling, auxin serves in
organogenesis, cell development, and differentiation. Especially
in the organogenesis of roots, for example, auxin enables cells to
determine their position and their identity. These multiple
functions of auxin demonstrate that identifying the momentary usage
(its semantics) is extremely difficult because the context
(investigation object of pragmatics) of use can be very complex and
highly diverse, although the chemical property remains the same.
Yes, mathematics is an artificial language. Last century the
Pythagorean approach, mathematics represents material reality, (if we
use mathematics we reconstruct creators thoughts) was reactivated:
Exact science must represent observations as well as theories in
mathematical equations. Then it would be sure to represent reality,
because brain synapse logics then could express its own material
reality. But this was proven as error. Prior to all artificial
languages we learned how to interconnect linguistic utterances with
practical behavior in socialisation; therefore the ultimate
meta-language is everyday language with its visible superficial
grammar and its invisible deep grammar that transports the intended
meaning. How should computers extract deep grammar structures out of
measurable superficial syntax structures? In the case of ENCODE
project (to find the human genome primary data structures) this was
the aim which got financial support of 3 billion dollars with the
result of detecting the superficial grammar only, nothing else.
Best Wishes
Guenther
Am 24.09.2015 um 07:47 schrieb Emanuel Diamant:
Dear FIS colleagues,
As a newcomer to FIS, I feel myself very uncomfortable when I have to
interrupt the ongoing discourse with something that looks for me
quite natural but is lacking in our current public dialog. What I
have in mind is that in every discussion or argument exchange, first
of all, the grounding axioms and mutually agreed assumptions should
be established and declared as the basis for further debating and
reasoning. Maybe in our case, these things are implied by default,
but I am not a part of the dominant coalition. For this reason, I
would dare to formulate some grounding axioms that may be useful for
those who are not FIS insiders:
1. *Information is a linguistic description of structures observable
in a given data set*
2. Two types of data structures could be distinguished in a data set:
primary and secondary data structures.
3. Primary data structures are data clusters or clumps arranged or
occurring due to the similarity in physical properties of adjacent
data elements. For this reason, the primary data structures could be
called physical data structures.
4. Secondary data structures are specific arrangements of primary
data structures. The grouping of primary data structures into
secondary data structures is a prerogative of an external observer
and it is guided by his subjective reasons, rules and habits. The
secondary data structures exist only in the observer’s head, in his
mind. Therefore, they could be called meaningful or semantic data
structures.
5. As it was said earlier, *Description of structures observable in a
data set should be called “Information”. *In this regard, two types
of information must be distinguished – *Physical Information and
Semantic Information*.
6. Both are language-based descriptions; however, physical
information can be described with a variety of languages (recall that
mathematics is also a language), while semantic information can be
described only by means of natural human language.
This is a concise set of axioms that should preface all our further
discussions. You can accept them. You can discard them and replace
them with better ones. But you can not proceed without basing your
discussion on a suitable and appropriate set of axioms.
That is what I have to say at this moment.
My best regards to all of you,
Emanuel.
--
-------------------------------------------------
Pedro C. Marijuán
Grupo de Bioinformación / Bioinformation Group
Instituto Aragonés de Ciencias de la Salud
Centro de Investigación Biomédica de Aragón (CIBA)
Avda. San Juan Bosco, 13, planta X
50009 Zaragoza, Spain
Tfno. +34 976 71 3526 (& 6818)
pcmarijuan.i...@aragon.es
http://sites.google.com/site/pedrocmarijuan/
-------------------------------------------------
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