Genes, Morphogenesis, Evolution: Life and ALife Aspects
Modelling the intra-
and intercellular signalling networks
The main problems encountered in the investigation and modeling the
intra- and intercellular signaling networks are the presence of big number
of parameters which will be difficult to test. The necessary experimental
techniques for the massively parallel measurements of biochemical parameters
are neither available nor possible to reach in the foreseeable future.
The Boolean network theory enables to consider the biological systems as
the projection in intercellular signal space, protein activity space or
gene expression space. Once the variables have been defined in a particular
parameter space, other elements can be folded onto the functions governing
these parameters. From the view of genetic networks, all events on the
level of production of signaling molecules, protein phosphorylation etc.
will end up in determining which genes are activated or inactivated [11].
Based on cooperativity and threshold behavior, the binary simplification
may also be extended to these biochemical interactions [12].
Therefore the computation of extended networks could be achieved by including
all higher level molecular functions in the formulation of wiring diagrams
and Boolean rules. For instance a gene encoding a signal molecule synthesizing
enzyme may exert a positive feedback on its own production, provided the
genes for its receptor and the necessary intercellular signal transduction
molecules are active.This would correspond to and connections between
the involved elements. Such a feedback mechanism has been considered for
the regulation of GAD (glutamic acid decarboxylase; catalyzes the synthesis
of the neurotransmitter GABA) in the developing rat spinal cord [13] GAD
acts through the diffusible intercellular signal GABA (gamma amino butyric
acid), and signaling mechanisms involving GABA receptor operated Cl-channels,
possibly Ca(2+) channels, Ca(2+) dependent protein kinases and phosphorylation
activated transcriptional regulators. This signaling chain could lead to
the activation of GAD mRNA expression. From a Boolean network standpoint
it would suffice to simplify this scheme into a rule that incorporates
the exact combination of expressed genes; the expression of a gene is reduced
to a function of the expression of genes. Relative to the genetic network
perspective, proteins will inadvertently execute their function, no matter
how intricate and are only relevant from the standpoint of the computation
of the state as defined by the gene expression pattern.
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