Skip to main content
Figure 4 | BMC Systems Biology

Figure 4

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

Figure 4

Experiment 1: We use the observed data to estimate μ p = m a v e p a v e = 4.9783 144.8241 = 0.0344 MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaeqiVd02aaSbaaSqaaiabdchaWbqabaGccqGH9aqpjuaGdaWcaaqaaiabd2gaTnaaBaaabaGaemyyaeMaemODayNaemyzaugabeaaaeaacqWGWbaCdaWgaaqaaiabdggaHjabdAha2jabdwgaLbqabaaaaOGaeyypa0tcfa4aaSaaaeaacqaI0aancqGGUaGlcqaI5aqocqaI3aWncqaI4aaocqaIZaWmaeaacqaIXaqmcqaI0aancqaI0aancqGGUaGlcqaI4aaocqaIYaGmcqaI0aancqaIXaqmaaGaeyypa0JaeGimaaJaeiOla4IaeGimaaJaeG4mamJaeGinaqJaeGinaqdaaa@51B4@ . We use the data points representing m max = 7.136, m min = 3.092, p max = 171.9 and p min = 110.3 to calculate B A = 7.136 − 3.092 171.9 − 110.3 = 0.0656 MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaqcfa4aaSaaaeaacqWGcbGqaeaacqWGbbqqaaGccqGH9aqpjuaGdaWcaaqaaiabiEda3iabc6caUiabigdaXiabiodaZiabiAda2iabgkHiTiabiodaZiabc6caUiabicdaWiabiMda5iabikdaYaqaaiabigdaXiabiEda3iabigdaXiabc6caUiabiMda5iabgkHiTiabigdaXiabigdaXiabicdaWiabc6caUiabiodaZaaakiabg2da9iabicdaWiabc6caUiabicdaWiabiAda2iabiwda1iabiAda2aaa@4BAB@ .

Back to article page