The transfer of biological and
natural world phenomena via algorythms into computing and autopoietic
systems is a core challenge for OPAALS. Here, some of those involved in
this work report on key aspects and their approach to providing a
common framework, largely inspired by systems theory, that will help
organise the research of the project in both its social science and
computer science domains.
1. Experimental work on the p53-mdm3 regulatory cycle
p53 is perhaps the most important
and best characterised tumour suppressor protein. As such, its primary
function is to stop proliferation and/or kill damaged cells. Hence, its
levels and activity are tightly regulated through a negative feedback
loop mechanism. p53 is known to induce the synthesis of its negative
regulator mdm2. mdm2, which itself has a very short half-life,
interacts with p53 and functions as an E3 ubiquitin ligase that
promotes the conjugation of p53 to ubiquitin. This modification
effectively targets p53 for degradation. Contributing to its 'anti-p53'
function, mdm2 is also thought to impair the activity of p53 by masking
its transactivation domain. In response to stresses (e.g. DNA damage)
the interaction of p53 with mdm2 is impaired and p53 accumulates
leading to a halt on cell proliferation or to the induction of cell
death by apoptosis. Furthermore, p53 levels have been shown to
oscillate in response to DNA damage. Whether these oscillations are
digital is still a matter of debate.
We have identified a series of mdm2
mutants that are deficient at degrading p53. As mentioned above, mdm2
levels are increased through p53’s ability to increase Mdm2
gene expression. Additionally, mdm2 levels can be increased through the
simple interaction of p53 with mdm2. Supporting this, small molecules
that mimic p53 binding to mdm2 lead to an elevation in mdm2 levels. We
observed that unlike the levels of wild type mdm2, the levels of the
mdm2 mutants we study are not effectively increased by interaction with
p53. This implies that the interaction of mdm2 with p53 causes a
conformational change or modification on mdm2 that protects it from
degradation and that this change cannot occur with the mdm2 mutants.
By expressing this new concept
mathematically we have developed a set of equations that lead to an
oscillatory behavior of p53 and mdm2 levels in response to stress. This
oscillatory behavior is lost when we the term expressing the
stabilization of mdm2 by its interaction with p53 is omitted.
|
 |
Image 1
Expressing
increasing amounts of wild type mdm2 (wt mdm2) decreases p53 levels in
cells. This decrease is significantly impaired when an mdm2 mutant
(EVEmt) is used. Note that the levels of the mdm2 EVE mutant are lower
than the levels of wild type mdm2. |
Image 2
mdm2
levels in cells are increased in the presence of nutlin-3, a small
molecule that mimics the binding of p53 to mdm2. The levels of the mdm2
EVE mutant are less effectively induced by nutlin-3. b-gal is a control
protein that does not respond to nulin-3 and is used to evaluate the
quality of the procedure. |
2. SBML as a bridge between Systems Biology and Software Engineering
Biomimicry
in engineering is a long established process, and probably
started with Leonardo Da Vinci’s during the renaissance, with his
flying machine designed around the anatomical structure of birds.
Despite his genius it is still debated as to whether his flying machine
would have flown, which provides a reminder that such research may not
be a straight forward process.

Diagram showing the Biologically Inspired Design Process
Nature has been in the research business
for 3.8 billion years and in that time has accumulated close to 30
million “well adjusted” solutions to a plethora of design challenges
that humankind struggles to address with mixed results. Biomimicry is
an emerging discipline that seeks sustainable solutions by emulating
nature’s designs and processes. There are some great opportunities to
learn how Nature has designed elegant solutions for some tough
human-made problems.
In the DBE project we researched using
biomimicry in computing engineering to create the Evolutionary
Environment Software Ecosystem, mimicking the processes of evolution
and ecosystems to create an Ecosystem-Orientated Architecture
(EOA). Despite its success, the key distinction between our
software ecosystem (EvE) and a biological ecosystem could be stated
succinctly as a lack of autopoiesis, which is a construct for
self-organisation of biological ecosystems. To create a digital
ecosystem that demonstrates autopoiesis, we will need to determine the
design patterns of the autopoietic constructs and algorithms common to
all biological ecosystems. "In software engineering, a design
pattern is a general repeatable solution to a commonly occurring
problem in software design. A design pattern is not a finished design
that can be transformed directly into code. It is a description or
template for how to solve a problem that can be used in many different
situations. Object-oriented design patterns typically show
relationships and interactions between classes or objects, without
specifying the final application classes or objects that are involved.
Algorithms are not thought of as design patterns, since they solve
computational problems rather than design problems." Extending
this concept, Biological Design Patterns (BDPs) will catalogue common
interactions between biological structures using
a Pattern-Orientated Modelling (POM) approach, which here will
provide autopoiesos. These BDPs could eventually be applied to our
software ecosystem to endow it with the same
self-organising capabilities found in biological
ecosystems, and one of the ways in which this will be evident will
be the ability to apply the evolutionary process at a lower level
of granularity than previously possible, i.e. the
object and method level, instead of the service level as is currently
done. We are currently focusing on intracellular behaviour for the
BDPs of our interactive model of computing, because cells are
fundamental to the autopoietic behaviour inherent in life, being
the basic unit for the construction of all life and which operate
almost entirely through the process of gene expression. Cells are
the biological construct that most obviously show autopoietic
behaviour, which is a process working similarly a multiple levels
of scale, and so an understanding of cellular operations is a
critical first step in providing an tangible understanding of
autopeiosis. To this end we will develop a modelling framework based on
the Systems Biology Modelling Language (SBML), which utilises a domain
modelling methodology based on UML to represent biochemical pathways.
"This UML-based definition in turn is
used to define an XML Schema (Fallside, 2000; Thompson et al., 2000;
Biron and Malhotra, 2000) for SBML. There are three main advantages to
using UML as a basis for defining SBML data structures. First, compared
to using other notations or a programming language, the UML visual
representations are generally easier to grasp by readers who are not
computer scientists. Second, the visual notation is
implementation-neutral: the defined structures can be encoded in any
concrete implementation language—not just XML, but C, Java and other
languages as well. Third, UML is a de facto industry standard that is
documented in many sources. Readers are therefore more likely to be
familiar with it than other notations."
This framework includes a translator
from the specified chemical reactions to the corresponding differential
equations for the time-evolution of the concentrations of the reactants
and products. Differential equation models can then be investigated in
Mathematica and other similar packages. Whereas we hope that this
approach will help UNIVDUN’s research in the modelling of cell
regulatory cycles, the benefit arises mainly from the use of a domain
modelling methodology that is based on UML. In other words,
strengthening the formal and semi-formal language links between biology
and software engineering.
3. Mathematical framework for interaction computing
We are examining some ideas related to
the connections between cell biology and software security. This work
is being done in collaboration with the BIONETS project ( www.bionets.org)
where Daniel Schreckling, a researcher in software security from the
University of Hamburg, is showing a similar interest to develop a
biologically inspired mathematical framework for interaction computing.
From the point of view of OPAALS, therefore, software security
represents a potential field of application of the theory. The fact
that Digital Ecosystems research is currently weak on security aspects
makes this collaboration particularly welcome.
The bridge that we are in the process of
building between these two very different fields relies on abstract
algebra and logic and can be simplistically depicted as follows:
cell biology - algebra - logic - security
In this context security represents one
of the possible applications of a formalism that we expect to be of
wider relevance. When referring to biologically inspired computing,
reliance on some kind of evolutionary framework tends to be assumed by
default. Whereas biological evolution does represent an essential model
for biologically inspired computing, in this work we are focussing on
the ‘other’ function of DNA. By this we mean all the processes relating
to the life of the individual organism, thus a better name could be
‘development’, or ‘morphogenesis’, or ‘gene expression’.
As noticed by Crick and Watson
themselves, it appears that the DNA code has a non-trivial and
non-random formal structure. In the last 20 years or so several models
have been proposed, with the latest ones going beyond a Boolean
algebra, to a Lie algebra. A Lie algebra is a vector space whose
elements satisfy certain properties with respect to a binary operator
called a ‘commutator’. The DNA code of 64 codons is in fact a Galois
field extension (and therefore a finite vector space) most of whose
quotient fields provide taxonomies for well-known physico-chemical
characteristics of the corresponding amino-acids. Foremost is
hydrophobicity, which is directly related to protein folding structure,
which in turn is related to protein function.
Our current activities are focussed on
understanding the abstract algebra and its connections to non-standard
logics. The objective is to reach a mathematical model that can
formalise the stable interactive behaviour of the cell components into
an organisationally closed system that represents the archetype
autopoietic system (i.e. a stem cell). Because cell biology is
fundamentally digital, our hope is that by formalising cell-biological
structure and behaviour in this manner we will arrive at the
Interaction Machine model of computation as the kernel of digital
autopoietic systems.
4. In Principio Erat Verbum
In 1917, D’Arcy Wentworth Thompson was
appointed to the Chair of Natural History in St Andrews University.
Thereafter, several times a day for the next 30 years, he passed
through an archway which led both to the Bell Pettigrew Museum (where
he worked) and to St Mary’s College. Above the archway are the words
from the opening sentence of the gospel according to St John’s “In Principio Erat Verbum”—In the beginning was the word.
We have to start with words because,
otherwise, all will end in confusion. The OPAALS project brings
together researchers and practitioners from a broad variety of
disciplines. We all have our own specialist vocabularies: our
discipline-specific words; our own specific meanings for words in
common use. We each bring understanding of our own discipline and the
potential to misunderstand, or entirely fail to comprehend, the
disciplines of others. The clear definition of the terms used in
biology, as it applies to the OPAALS project, has therefore been an
important initial task for WP1 and the clear presentation of such
definitions is an important component of our first deliverables (at
Month 18).
Following the first review, the
reviewers have asked for a paper that can serve a similar function to
orient the project toward an overarching or we could even say
archetypal model of an Autopoietic Digital Ecosystem. We expect this
paper to lay the groundwork for a theory of autopoiesis in computing,
which is likely to be based on some form of interaction computing. At
the same time, the paper will also review and begin to assess the
application of autopoiesis and systems theory to social science
disciplines. Interestingly, such adoption by social science of concepts
from second-order cybernetics has been strongest in the field of
linguistics and philosophy of language. The strongly relativist
philosophical stance upon which Maturana and Varela based their theory
is in fact perfectly compatible with the inter-subjective construction
of reality of social constructivism.
http://freethinkr.wordpress.com/2007/06/
http://en.wikipedia.org/wiki/Design_pattern_(computer_science)
http://sbml.org/specifications/sbml-level-2/version-1/html/sbml-level-2.html