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Table 2 Experiment 2 (Hirata Data).

From: Bifurcation analysis informs Bayesian inference in the Hes1 feedback loop

θ

sp1

sp2

sp3

σ

acc rate

R ^ MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGafmOuaiLbaKaaaaa@2D12@

P 0

99

103

103

0.55

29

1.0000

n

5

4.8

5.3

0.7

34

1.0003

μ m

0.028

0.03

0.03

0.3

28

1.0001

μ p

0.028

0.03

0.031

0.5

31

1.0002

Ï„

18

19

18.5

0.5

27

1.0001

k s

2.5

2.2

2

0.2

27

1.0000

  1. This table shows inputs and convergence information for 3 illustrative MCMC chains. For each parameter, θ we show the starting point (sp) of the Markov chains (columns 2–4), variance σ of the Gaussian proposal function (column 5), the acceptance rate (column 6) and statistic R ^ MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGafmOuaiLbaKaaaaa@2D12@ (column 7).
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BMC Systems Biology

ISSN: 1752-0509

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