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Table 1 Required system integrations, equations used, and sources of error.

From: A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

Method

System Integrations

ROSA

SOSA

Equations Used

Error Sources

MC

2L(J + 1)

264000

288000

(10)-(12)

• number of MC samples used

DA

2J(J + 1) + 1

925

1105

(14)-(16)

• local approximation

     

• truncation of Taylor series

     

• derivative approximation

PA

J(J - 1)S2/2 + JS + 1

3445

4141

(14), (15), (18)

• local approximation

     

• truncation of FD-HDMR

     

• polynomial approximation

     

• polynomial regression

GHI

2J(J - 1)⌊Q/2⌋2 + 2J⌊Q/2⌋ + 1

3445

4141

(14), (15), (19)-(21)

• local approximation

     

• truncation of FD-HDMR

     

• Gauss-Hermite integration

OHA

L

6000

6000

(14), (15), (23)

• truncation of ANOVA-HDMR

     

• Hermite approximation

     

• polynomial regression

  1. L: number of Monte Carlo (Latin hypercube) samples.
  2. J: number of biochemical factors.
  3. S: number of regression samples per factor.
  4. Q: order of Gauss-Hermite integration.