The Origin of Life through Network Evolution

Rick I. Majpruz rimajpuz at
Mon Jan 13 00:15:06 EST 1992

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I am Rick Ivan Majpruz of Waterloo, Canada.  To the fullest extent of
the law, I hereby claim all intellectual property rights on all nations
of this Earth for the concepts expressed in this document and derived
from this document.  You may read this document; all other permissions
are denied.  It is now 12:15 AM on Monday, January 13, 1992.

* Title : The Origin of Life through Network Evolution

* abstract

This paper fills in a ***billion year gap*** in our knowledge of the
world.  First, the science of biology is placed on a purely mathematical
basis.  Then it will be shown that evolution began as soon as the oceans
had cooled enough to support chemical reactions in that chemical soup.
This evolution was done by having networks of chemicals copy themselves
in the soup through the process of network evolution.  Good network
functions are retained and built up in the soup.  The chemical
interactions increased in complexity through small changes occuring over
long periods of time (evolution).  Various cellular features arose
independently and finally merged into what is now called the
`protocell'.  The top level of chemistry was absorbed by a simple cycle
around DNA.  The very process of mutation is a feature that `evolved'.
But the idea of there being an original protocell is false.  Thus
abiogenesis is an inexact dividing line between, on one hand, a form of
life not bound by cell walls and, on the other hand, what current
biological doctrine now considers to be life.

* other useful results

A clear theoretical justification for the *environmental* movement is
given.  A powerful network-based model could probe the interactions of
diffuse life such as the *AIDS virus*.  This gives new mechanism to
explain *cancer* and *aging* and various so called *genetic diseases*.
This model suggests powerful new *economic* models to understand the
effects of innovation, the flow of materials, or many other economic
activities.  And a possible explanation for the filament structure of the
*universe* is given.

* the network evolution model

For those who haven't taken university level mathematics, all this
`network' stuff is mathematics.  Just watch how logical and methodical
the material is in this paper; you'll see that simple high-school
biology, including evolution, has indeed been expressed in a purely
mathematical fashion.

** intellectual property protection

I am Rick Ivan Majpruz of Waterloo, Canada.  To the fullest extent of
the law, I hereby claim all intellectual property rights on all nations
of this Earth for the network evolution model.

** the network

Let there be a group of non-unique elements.  Let there be a process
which takes an input element from the group and generates an output
element from the group and operates with a given speed.  It will be
assumed that the processes act on the elements in some regular manner
called entropy.  Imagine a series of these processes feeding into one
another and forming a cycle or feedback loop.  Now visualize this cycle
as a gear turning.  The speed of the cycle is the speed of the slowest
process in that cycle.

But several feedback loops may interact.  That is, the turning of one
cycle will drive the turning of another cycle through outputs used by
the second cycle.  This can be visualized as the turning of two gears
with interlocked teeth.  For a large number of cycles, it is best to
think of these cycles embedded in a large network of interacting
processes.  The network can be divided into subnets.  Note that a subnet
of a network is also a network.  The speed of a network is the speed of
the slowest cycle.

** network qualities

Let an object be an element, process, cycle, subnet, or the entire
network.  Come up with some parameters that rate the network `quality'
of an object.  For example, the following are valid qualities:

    rate at which element reproduces itself in the network
    or rate at which a process can handle elements
    or rate at which the cycle turns
    or rate at which a subnet turns

Any quality which can be described mathematically may be used as a

** capacity

The capacity measures the degree to which an object is considered good.
A capable object is an object with a high capacity.  This is determined
by combining the individual qualities of an object.

Mathematically, this combining is done as follows.  Assign the above
qualities to axes of a multidimensional space called the quality space.
Draw the line with the coordinates (x,x,...,x).  Call this line the
quality axis.  Determine the location of a given object in this space
called its quality point.  Find the plane which contains this location
and is perpendicular to the quality axis.  Called this the quality
plane.  Let the intersection of the quality plane and the quality axis
be at (y,y,...,y).  Then the capacity of the object is `y'.

To generate a useful quality index, it may be a good idea to avoid
parameters which are linear combinations of one another.

** innovation

Separate the network into subnets appropriate for analysis.  These
subnets may share elements and processes.  The choice of these subnets
is left to the user of this model.  Ideally, the user should get some
useful view of the network.

Determine the capacity of each subnet and rank accordingly.  Notice that
any qualities of the quality space are also qualities of capable
subnets.  Subnets with lower capacities drive higher subnets through the
objects they output.

Sometimes, a subnet will operate in some interesting way.  If this is the
case, call this interesting way a function.  Notice that the capacity of
functions can be determined or at least estimated.  A subnet is not
considered to exist until it is going above some user defined speed.
Innovation is when the network happens to generate a subnet with a
capable function.

Something is virtual when it isn't around all the time but will be
around enough to have some noticable effect.  For networks dominated by
constant chaotic innovation, new subnets will spontaneously arise and
collapse in a virtual fashion.  In time, the network will eventually
manifest essentially deterministic large scale effects.

This is done by building transitory higher level subnets on top of the
outputs of lower subnets.  Once the higher level subnets have gone
through a shakedown period, the next round of higher level subnets will
arise.  That is, chaos is transformed into complexity and an innovating
network results in an evolving network.  This process is called

** synthanet

Capable functions are usually ignored until serendipity causes them
affect the network.  But theoretically, given time and material, any
subnet can be produced to go at any speed.  This property of the network
is `synthanet'.  Let `funcnet' be a part of the net which can be
interpreted as performing some net function `func'.

** constructs

Constructs are elements arranged into subnets with a limited degree of
inputs and outputs.  If there is a small number of elements that
directly affects the speed of a construct then call this a prime element
and call the construct a prime construct.  Then the population of prime
constructs is proportional to the number of prime elements.  A number of
constructs with prime elements that differ slightly shall be called a

** history

By breaking down the network into various functions and constructs,
interpretations can be given to the motion of elements on a large scale.
Then the following types of questions can be asked:

    How did the network get to this stage?
    Where is the network right now?
    Where is the network going?

Through this, a history of the evolution of a network can be interpreted
and general processes/principals can be determined.

*** history depends on the perspective of the future

Given a chaotic system, it will be difficult to track down the sources
of important events.  Indeed, the start of a given source can seem quite
minor and random and only becomes important from the perspective of the
future.  Looking from the future, we impose a pattern or history.  One
slight twist in another direction and something else could easily have

*** punctuated evolution

Evolutionary potential accumulates as a subnet begins to turn faster.
Then a mutation of a prime element sparks a sudden shift in the
equilibrium.  This is punctuated evolution.

*** predator-prey model

One type that depends on a second type for inputs is called a predator
and the second type is called prey.  Then, the number of predators
should be found to vary with the number of prey in a delayed sinusoidal
curve.  This assumes a constant supply of inputs to the prey and a
constant breaking down of the predators' prime elements.

*** contraction

When all prime elements of a given type disappears, this is called
contraction.  In a network of interdependent types, the contraction of
enough types will cause a chain reaction of contractions called mass
contraction.  At some point, the mass contractions will begin to bottom
out and the network will begin to rebuild.

* life : an instance of network evolution

In this section, various phenomena found in life will be represented by
the mathematics of the previous section.  Once defined, the phenomena
will be treated as if they are mathematical objects themselves.  Then,
other phenomena in the life sciences will be derived mathematically.

** diffuse evolution

*** biosphere

Let a biosphere be any planet with the potential for life.  The
biosphere operates according to the principals of network evolution.  A
biosphere element is a chemical.  A biosphere process is a chemical
reaction.  The rate at which a chemical reaction takes place is
proportional to the quantity of inputs.  An input of particular
importance is the catalyst.

*** biological qualities that enchance self-perpetuation

Some of the useful qualities of objects in the biosphere are:

    usefulness for other objects
    ease of spontaneous generation
    space in which object can operate
    number of objects in existence
    ability of object to mutate

*** diffuse evolution

After the biosphere collected from interstellar matter, the surface
cooled and oceans formed on its surface.  Once the oceans became cool
enough, interesting chemical reactions took place.  Biological
innovation is done with virtual chemistry.  Virtual chemistry is
chemistry in which the right chemicals are ready at the right time to do
the desired reaction.  However, the inputs and outputs need not persist
in the environment for any long duration but, over time, they do have a
tangible effect on the net especially for lower level subnets.  Virtual
chemistry is driven by entropy and chaos.  Entropy comes from the energy
of the sun.  Chaos comes from the randomness of quantum mechanics.
Virtual chemistry is the source of innovation of biosphere evolution.
Thus, evolution began immediately after the oceans cooled.

Indeed, the activity of virtual chemicals are conceptually similar to
the virtual particles of quantum physics.  Diffuse organisms are
organisms which are spread throughout the biosphere.  Diffuse evolution
operates on diffuse organisms.  By definition, the biosphere is a
diffuse organism.  It is not clear if there were multiple diffuse
organism in the biosphere.  Diffuse evolution is driven by virtual
chemistry.  Biological contraction is extinction.  Biological mass
contraction is mass extinction.

*** capable functions persist in the biosphere

Diffuse evolution likely had many stages causing many mass extinctions.
But there is fuzzy line between each of these stages because the
chemicals are diffusely spread out.  Thus many extinctions are long,
drawn-out events.  Thus capable functions persisted in the biosphere.

Slow change is like aggressive empires slowly spreading through the
world.  Rapid change is like an important news event spreading rapidly
through the media.  If the waters of the early biosphere were basically
tranquil then functions would spread in the first fashion.  If the
waters of the early biosphere sloshed around then functions would spread
in the second fashion.

*** the spontaneous generation of capable chemicals

Through synthanet, some subnets have the function of generating a
specific chemical.  Assume that the subnet performs the function `func'.
Then the name of such chemicals are funcchems.  Funcstruct is a set of
funcchems that can be combined together into specific structures.  This
is like a shoe factory (the shoenet) building a range of shoes
(shoechems) of various brands (shoestruct).  A set of these functructs
(a shoe from each brand) is called referred to as the alphabet of the

*** disruption zones

The operation of the biosphere is just a snapshot view of a system
reaching equilibrium.  Now consider the motion picture.  Disruption
zones are geographical locations of various sizes where the highest
levels of the net collapse.  Causes of disruptions are:

    volcanic activity
    solar radiation
    meteor impacts
    zones where the network sponteneously collapses (eg forest fire,death)

Subnets compete for recolonization of disruption zones.  The constant
disruption keeps a supply of raw materials.  During early diffuse
evolution, this will occassionally produce additional chemicals for the
higher level subnets.  These disruption zones supply energy.  This
energy is an important reason for the rising information content of the

*** junkokay / the generation of less useful chemicals is not a problem

Often subnets will generate chemicals that never enhance the survival of
that particular subnet.  This is especially true for the early biosphere
where many subnets mostly generate chemicals that never serve any
identifiable purpose.  But this is acceptable because most early subnets
are inefficient.  Thus, many less capable subnets would not be selected
against in the early biosphere.  They would be protected by the
inefficiences of the entire environment.  This is the junkokay property
of the biosphere.

Indeed, this spurious generation of chemicals will sometimes result in
powerful, new higher-level subnets.  From the arbitrary perspective of
the evolution of later life, there were always useless extra chemicals
drifting around in the early biosphere.  Junkokay is simply another
source of these extra chemicals.

** capable functions in diffuse evolution

Using only small steps and synthanet, the biosphere will accumulate a
wide variety of subnets with capable functions.  The following sections
presents a range of useful subnets.  It may be that the biosphere is
divided into various diffuse organisms that use functions such as these.
Then one could take the view of these functions competing.  Then more
capable versions of these functions emerge.

One of the qualities of life is that it is useful to other life forms.
Thus, any hypothetical diffuse organisms would have to be able to use
the outputs of a capable function.  Thus, the most powerful functions
are not necessarily the best at surviving because of the opportunistic
nature of life.

These subnets likely arose in many places and for many times and those
that were the best at persisting in the biosphere came together to form
the first protocells.

*** jigsawchem / concentrating network material

Jigsawchems are chemicals that fit together like jigsaw pieces.  This
has the effect of forming into large sheets.  Sheetnet could have arisen
which would have catalyzed this sheet forming process.  This molecular
driftnet causes chemicals to accumulate on both sides of it.  It
collects the other chemicals into greater concentrations.  Then the
sheets begin to fold and turn in on themselves which causes chemicals to
be even more effectively trapped in crevices.  Finally, the edges of
these sheets get sewn up together into crude leaky bags.

Each stage of jigsawchem usage results in ever greater concentrations of
the biosphere chemicals.  Also, these sheets protect more delicate
chemicals from the hard ultraviolet radiation of the early biosphere.
This is very useful before the presence of the ozone layer.  (The ozone
later is generated from oxygen which, in turn, is generated by
photosynthesis; therefore, it would not be present in the early
biosphere.)  After jigsawchem, many reactions take place at higher
levels of the ocean.  Those reactions benefit from greater energy

All this speeds up the rate of evolution.

*** controlnet / regulating other network functions

**** negative feedback as a regulating mechanism

The generation of one function, xnet, may interfere with the operation
of a second function, ynet.  Xnet could do this by consuming an input of
ynet.  But if xnet requires the output of ynet then this will eventually
slow down xnet also.  Depending on the comparative capabilities of xnet
and ynet, this could form various kinds of regulating mechanisms.  This
interaction shows one way in which subnet interaction could be used to
regulate the actions of high level subnets.

This speeds up the rate of evolution.

**** slow subnets as a regulating mechanism

A slow operating subnet could, over time, become a capable function.  It
could provide some essential function and thereby keep higher level
subnets going at a constant, regular pace.

This speeds up the rate of evolution.

*** enerchem / providing an energy source for the network

A enerchem is a chemical that acts as some standardized source of quick
energy.  Some larger subnet may use controlnets to regulate the use of
this chemical and keep it in steady supply.  Chemically, the enernet is
anti-entropic.  From the perspective of chemistry, life violates entropy
at a local level.  But, once physics (the shining sun and other external
energy sources) has been factored in, entropy is no longer violated.

This speeds up the rate of evolution.

*** buildachem / providing capable structures for the network

The buildachem is a chemical used to provide capable structures for the
network.  These structures are built by stringing together a sequence of
distinct, simpler buildastruct chemicals.  Even tiny structures can be
useful.  Structures can contain, hold, catalyze, or perform endless
functions.  Once these structures begin to feed into their own subnets,
they become a self-perpetuation system.  They will also generate
spurious outputs which then affect other subnets, sometimes in capable
fashions.  A high number of buildastructs are useful.  Note that the
generation of spurious buildachems are acceptable because of the
junkokay property.

This speeds up the rate of evolution.

*** infochem / concentrating network information

The infochem is a chemical used to store information.  Information
storage is done by stringing together a sequence of distinct, simpler
infostructs.  The infochem could be used in various ways such as a
library to store information or as a messenger to transport information.
The presence of less capable infochems is acceptable because of the
junkokay property.

Even an infochem two infostructs long with an alphabet of two characters
is useful.  This is because a regular pattern will help with ordering
during the building of certain chemicals.  Seen from this perspective,
the infochem is a catalyst.

The infochem is a way to concentrate the information found in the
chemical network.  That is, a single infochem will replace whole subnets
of chemicals.  During the recolonizing of a disruption zone, capable
chemicals must arrive before carrying out capable functions.  But, with
infochems, fewer chemicals need to arrive.  Thus, infochems speed up the
recolonization of disruption zones.

This speeds up the rate of evolution.

**** copynet / copying infochems

Copysubnet copies infochems.  A simple way to provide copying is to
evolve infochems with something called a copy-latch.  Given an alphabet
of infostructs {A,B,C,A',B',C'}, there could be a direct copy-latch or
an invert copy-latch.

A direct copy-latch would match up A with A, B with B, C with C, A' with
A', B' with B', and C' with C'.  An invert copy-latch would match up A
with A', B with B', and C with C'.  But the copy-latch would have the
property of weak bonds and not remain attached.  Then, every so often, a
copy of an infochem would arise.  With an invert copy-latch, the process
would have to repeat itself before a useful copy of the infochem is

Copynets would speed up the process.  To further speed up the process,
an unzipnet could work with the copynet to Separate the infochem copies
once they are made.  Later, the initial copynets and unzipnets could be
replaced with single, complex copychems or unzipchems.

This speeds up the rate of evolution.

*** the evolution of mutation / chance modification of the infochem

Initially, innovation took place throughout the entire biosphere via the
generation of new subnets.  But the biosphere produced high
concentrations of chemicals.  Thus, less robust infochems could survive
long enough to be used for a while.  Mutation is a type of virtual
chemistry in which brand new infochems are generated.  The term mutation
refers to process of mutation and to the mutated infochems that arise.

Because of junkokay, it is feasible for copynet to copy less capable
mutations.  Thus, mutation increases the capacity of the biosphere.
This indirectly affects the evolution of the biosphere.  Thus, mutation
is a form of innovation.  (Orthodox biology currently considers mutation
the entirety of innovation.)

This speeds up the rate of evolution.

*** the evolution of direct transcription

The infochem concentrates network information.  Buildachem provides a
wide range of useful chemicals.  More and more infochems and buildachems
are evolved by the network.  Thus, the subnets between some infonets and
some buildanets will eventually collapse.  Then, direct (or nearly
direct) transcription of infochems into buildachems will begin to take

This speeds up the rate of evolution.

*** subnet-snatch / infochems replace subnets

Subnet-snatch is when subnets become replaced by infochems.  Assume that
enough of a generalized subnet surrounds infochems.  Then subnet-snatch
will increase the rate of chemical interactions of its local area.  This
is because it will no longer be necessary to assemble a range of
chemicals required for that subnet.  Also, such chemicals will tend to
be physically closer to the infochems.  This will tend to increase the
rate of copying of the particular infochem.

This speeds up the rate of evolution.

** modern life

*** network fusion / collapse / shakedown

The network shrank at various times as capable functions gained
strength.  The information of the network was also concentrated onto the
infochem.  During the network fusion only a limited number of
infostructs and buildastructs survived.  The network fusion essentially
froze much of the potential evolution of life.  Metabolism is the
general chemical interactions of life performed inside of the cell.
Once the protocell became powerful enough, metabolism subnets external
to the cell wall completely collapsed.  But the network continued to
exist in the form of diseases, ingestion, excretion, respiration, etc..
This is the general interdependence of nature which continues to
demonstrate the network behaviour of diffuse evolution.

The infochems that survived are nucleic acid.  Nucleic acid is expressed
as DNA which is used as a library to store the information and RNA which
is used to transport the information.  The buildachems that survived are
the amino acids.  Amino acids are expressed as proteins which perform a
wide range of functions.  In DNA and RNA, four different nucleic acid
bases collected into sequences of three and were transcribed into
several dozen amino acids.  RNA has one differing nucleic acid base that
was retained during the shakedown period.

Thus, this combination of nucleic acid and amino acid concentrated the
chemistry of much of life into a simple cycle.  This simple cycle
generates enzymes (protein catalysts) that do the work of the now
collapsed network.  Cycles of protein transcribers, copiers, and
unzippers eventually became replaced by more complex efficient enzymes
to do the work.

*** the age of the localized organism and the persistence of viruses

Towards the end of the age of diffuse organisms, the jigsawchem sheets
were sewn into a tight ball.  This sealed the contents and prevented
them from just drifting away.  In particular, it collected and protected
the infochems which were increasing in value as copynet became capable.
Other functions also refined and interacted in various ways.  Thus, over
time, the various biosphere functions continued to refine themselves
until evolving into protocells, the first localized organism.

Localized organisms are organisms which are located at a precise
geographical location in the biosphere.  Many retain their contents
within cell walls, the modern refinement of jigsawchem.  The infochems
refined themselves until the nucleic acids (as incorporated by RNA and
DNA) took over.

Through network evolution, diffuse life generated localized organisms
which then came to dominate the biosphere at a macro-scale.  However,
diffuse life is still present in the form of viruses.  The modelling of
the spread of viruses could benefit by recognizing that they are diffuse

*** a reason for why there are no UFOs

One explanation to why alien lifeforms have not visited Earth is because
life in other biospheres never became localized.  Such life might never
feel the need to explore because it may not be aware of an external
world.  In addition, spliting off a section of itself and flinging it
into space might be as appealing as cutting off our arms and loading
that into the space shuttle.  Therefore, curious, localized,
transportable, intelligent organisms may be very rare products of the

*** the original protocell is a fiction

The section on capable functions in diffuse evolution lists various
components of the first protocells.  These components can arise
independently and be immediately useful to the biosphere.  Thus, it is
not possible to determine which cellular functions first arose in the
early protocells.  Also, each of these functions may have been evolved
many times.

The full support of the net is around during the generation of the
protocell.  Functions can exist separately in different
almost-protocells composed of many different chemistries.  Thus, just by
using the principals of network evolution, it is not possible to
determine which functions came first in the protocell.  With the power
of synthanet, any function could be shown to be the first function
operational in early protocells.

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