PNNL-13501 - Pacific Northwest National Laboratory

Development of Models of Cell-Signaling Pathways and Networks
Study Control Number: PN99020/1348
Joseph S. Oliveira, John H. Miller, William R. Cannon, David A. Dixon
This work focuses on development of the fundamental mathematics and model-building capabilities for a problemsolving
environment called the Virtual Cell. This research environment will culminate in the ability to model multiscale,
complex, whole-cellular processes with predictive capability for environmental signal recognition and response. The cellsignaling
model of the virtual cell provides us with a computational test bed that will enable an experimentalist to test
cellular processes computationally. This methodology will greatly enhance our capability to effectively understand and
control fundamental biological processes from a bioengineering systems point of view.
Project Description
Coupling theory and experiment to understand complex
cell-signaling networks requires a sophisticated appliedmathematical/computational-modeling
capability to
integrate back into the context of a functioning cell. In
addition, acquired knowledge is needed on signaling
kinetics, pathway cross-talk, protein structure/function
and interactions, and metabolism coupled to other
peripheral controlling and self-modifying phenomena.
The goal of this work is to develop the fundamental
mathematics and model-building capabilities for a
problem-solving environment called the Virtual Cell.
Three critical cell-signaling research issues have been
identified and validated by a variety of means. These
include 1) the need to analyze and understand the
subcellular components involved in cell signaling, 2) the
need to study cell signaling in vivo, and 3) the need to
synthesize the experimental knowledge and acquired
understanding into an integrated cellular context by the
development of models and computation. These three
research issues will also be used to further the
development of a suite of computational biophysics
problem-solving tools that links the multiscale biophysics
of cytoplasmic diffusive reactive molecular hydrotransport
to the emergence of both perturbative and
nonperturbative cell-signaling pathways. The future goal
is the construction of a computational biophysical systems
engineering test bed that will enable us to explore the
dynamic structure and function of cell complexes that
specialize into tissue assemblies and finally organ
transport systems.
Approach
Databases
A goal of this work is to continue to collect the available
experimental and model data on cell signaling, in order to
develop models. These data will be used to develop
models for some critical cell-signaling pathways, based
on an operations systems approach.
Petri Nets
The complex operational processes associated with cell
signaling—communications—lend themselves to being
faithfully modeled by Petri nets. A Petri net is a directed,
simply connected graph, composed of nodes (vertices)
and edges. Every Petri net has two types of nodes: state
nodes (S) and transition nodes (T). State nodes hold
information called tokens. Transition nodes define a set
of conditions that regulate the flow of information from
one state node to another; e.g., information from state S1
is transferred to state S2 when a set of transition
conditions T1 are satisfied.
Petri nets represent a rich mathematical framework for
modeling dynamically complex operational process
control systems. Every network ensemble provides us
with a number of discrete data abstractions for
representing an object and its attributes, together with a
set of constraints that determines the regulation of
complex operational processes. An incidence
(connectivity) matrix defines a framework for
Computational Science and Engineering 117