Team:LCG-UNAM-Mexico/Simulation

Simulation and parameter scan

Describir el comportamiento que queremos ver y por qué.
Incluir las gráficas de parameter scan, la gráfica de la vida, y el escaneo con el que definimos algunas constantes

Sensitivity analysis

Definir brevemente de que se trata, mostrar análisis a diferentes tiempos. Señalar los resultados que esperábamos y los que no

Stoichiometric matrix

Definir la información que contiene la matriz estequimétrica.
Definir los espacios nulos (link a wikipedia o matworld?)
Presentar las bases calculadas y una interpretación concisa

Steady-states

Definir estado estacionario, decir algo de la complejidad del problema y justificar la estrategia elegida (aproximación numérica)

Presentar la solución ontenida.

Jacobian

The Jacobian of a system is defined as the matrix of first order partial derivatives, ad it represents the best linear approximation to a function at a given point. In biochemical networks, the Jacobian can be defined for metabolites(Jx) or fluxes(Jv):

Where S is the stoichiometric matrix and G is the gradient matrix. S defines the structure of the network and has the stoichiometric coefficients of all reactions which are represented by the rows of S while metabolites are represented by columns. G is the matrix of first order derivatives of fluxes with respect to species concentrations:

This formal representation of the Jacobian formalizes the relation between the topology of the network, and its biophysical and kinetic characteristics (REFERENCIAS DE SUR UNO Y DOS).

For our system, we first obtained S which is rank deficient: its rank is 7 and it has 13 rows, this difference is explained by the moieties of the system. We reduced S to make it congruent with its rank by eliminating the rows corresponding to: AiiA, LuxR, pcI, p, Ni-ext and Unk. Then we constructed G as previously defined; the partial derivatives are calculated only with respect to the species that remained in S; the state at which G is calculated is the steady-state.

Both Jacobians were calculated and they were decomposed through similarity transformation of their eigenvalues and eigenvectos to obtain the modal matrices. This matrices represent the formation of molecular ‘pools’ on the system and the negative inverse of the eigenvalus represent the time scales at which this interactions occur. The Jacobians and modal matrices can be downloaded on Excel (.xls) format if you click here.

The values in the tables show that the nickel response is very fast, in the order of 6.03e-8 s, which is what we need to make this system and efficient transcriptional indicator. On the other hand, there is a pool of RcnA that forms immediately and another one that takes much more time to form.

REFERENCIAS DE SUR
Jamshidi N and Palsson (2008) Formulating genome-scale kinetic models in the post-genome era Molecular Systems Biology 4:171.
Jamshidi N and Palsson (2008) Top-Down analysis of temporal hierarchy in biochemical reactions networks PLoS Comput Biol 4(9).