Biology Reference
In-Depth Information
Table 1
A comparison of metabolic simulators with Petri nets approach
Gepasi
a
Jarnac
b
DBsolve
c
E-Cell
d
Tools
stoichiometry matrix presentation
+
+
+
+
Core algorithm and method
MCA
MCA
MCA
SRM, MCA
Pathway DB retrievable
−
−
WIT/MPW, EMP
KEGG, EcoCyc
Pathways graphic editor
−
+
+
−
Kinetic types
+ + +
++
++
+
Virtual cell model
−
−
−
+
Simulation graphic display
+++
++
+
+
Mathematical model accessible and modifiable
+
+
++
+
∗
SBML
∗
∗
∗
Data XML export
User interface
++
+
++
+
Programming language
C++
Delphi 5
C++
C++
a
Gepasi (
http://www.gepasi.org/
);
b
Jarnac (
http://members.lycos.co.uk/sauro/biotech.htm
);
c
Dbsolve (
http://homepage.ntlworld.com/igor.goryanin/
);
d
E-Cell (
http://www.e-cell.org/
);
∗
SBML (Systems Biology Markup Language) (
http://www.sbw-sbml.org/
) is a description language for
simulations in systems biology. It is oriented towards representing biochemical networks that are com-
mon in research on a number of topics, including cell signaling pathways, metabolic pathways, bio-
chemical reactions, gene regulation, and many others. SBML is the product of close collaboration be-
tween the teams developing BioSpice (
http://biospice.lbl.gov/
), Gepasi, DBSolve, E-Cell, Jarnac, StochSim
(
http://www.zoo.cam.ac.uk/comp-cell/StochSim.html
) and Virtual Cell (
http://www.nrcam.uchc.edu/
)
.
and most often without analytical solutions. This means that they can only be studied through numerical
algorithm, such as the Newton method for solving non-linear equations and numerical integrators. After
many years of development, now Petri nets have a mature mathematical algorithm and can solve NAEs
and ODEs and stoichiometric matrices. But biochemical systems are also rich in time scales and thus
require sophisticated methods for the numerical solution of the differential equations that describe them.
MATHEMATICAL METHODS AND ALGORITHMS
Kinetic models of metabolic networks are becoming imperative not only the knowledge of more and
more metabolic pathways has been acquired, but also the complexity of metabolic pathways requires an
analytical and quantitative solution. Kinetic models can provide us spatiotemporal scale approaches and
serve to check the consistency of metabolic theories with observed behaviors.
Related simulation environments
Many attempts have been made to simulate molecular processes in both cellular and viral systems.
Several software packages for quantitative simulation of biochemical/metabolic pathways, based on the
numerical integration of rate equations, have been developed. Table 1 shows a comparison of the most
well-known metabolic simulation systems.
Each tool possesses some prominent features while others little or no present. After a decade's
development, Gepasi is widely used both for research and education purposes to simulate biochemical
systems due to its powerful simulation engine and user-friendly interface. Jarnac, as a replacement
of SCAMP, has a nice pathway graphic editor, called Jdesigner, enabling users to interactively draw
a biochemical network. It has an SBW interface (System Biology Workbench), providing simulation
capabilities for alternative clients.
DBsolve is good at model analysis and optimization.
By using
