Systems Biology (Methods in Molecular Biology)

(Tina Sui) #1
JxðÞ¼,θ

∂Yðx,θÞ
∂ðx,θÞ

¼

∂y
∂x 1



∂y
∂xn



∂y
∂θ 1



∂y
∂θn
⋮⋮⋮⋮
∂ynu
∂x 1



∂ynu
∂xn



∂ynu
∂θ 1



∂ynu
∂θn

0 B B B B B B @
1 C C C C C C A

ð 7 Þ

the elements of the Jacobian matrix equals the coefficients of the
formal Taylor’s series expansion aroundt¼0 of the output sensi-
tivity derivatives with regard to initial conditions and parameters.
The sensitivity equations are:

X⋆
:

P
:x_ ¼ fðx,u,θÞ, xð 0 Þ¼x^0
d
dt

∂x
∂x^0 i

¼

∂f
∂x

∂x
∂x^0 i

,

∂x
∂x^0 i

ðÞ¼ (^01) n
d
dt
∂x
∂θi
¼
∂f
∂x
∂x
∂θi
þ
∂f
∂θi
,
∂x
∂θi
ðÞ¼ (^00) d
8




<


:
ð 8 Þ
The system
P⋆
can be solved iteratively generating truncated power
series solutions of desired order. Insertion into the output sensitiv-
ity expressions gives truncated power series:
d
dx^0 i
ytðÞ ¼
∂g
∂x
ðÞxtðÞ,utðÞ,θ
∂x
∂x^0 i
ðÞt
d
dθi
ytðÞ ¼
∂g
∂x
ðÞxtðÞ,utðÞ,θ
∂x
∂θi
ðÞþt
∂g
∂θi
ðÞxtðÞ,utðÞ,θ
ð 9 Þ
We may summarize the possible strategy with the following
diagram:

∂(Lifg) 0 ≤i≤ν
∂(x,θ) Symbolic
∂(Lifg) 0 ≤i≤ν
∂(x,θ) Numeric
x ̃x
θ θ ̃
u(t) u ̃(t)
x→x ̃
θ→θ ̃
u(t)→ ̃u(t)
2.3 Inverse Problem Let’s consider the computation of an approximation to a solution
of a nonlinear operator equation
FðxÞ¼y ð 10 Þ
74 Rodolfo Guzzi et al.



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