LEADER 01782oam 2200529 450 001 9910715136103321 005 20201222143641.0 035 $a(CKB)5470000002508655 035 $a(OCoLC)937438008 035 $a(EXLCZ)995470000002508655 100 $a20160208d1931 ua 0 101 0 $aeng 135 $aurbn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEffect of high air velocities on the distribution and penetration of a fuel spray /$fby A.M. Rothrock 210 1$aWashington, [D.C.] :$cNational Advisory Committee for Aeronautics,$d1931. 215 $a1 online resource (10 pages, 10 unnumbered pages) $cillustrations 225 1 $aTechnical note / National Advisory Committee for Aeronautics ;$vNo. 376 300 $a"May, 1931." 300 $aNo Federal Depository Library Program (FDLP) item number. 320 $aIncludes bibliographical references (pages 9-10). 606 $aAirplanes$xFuel systems 606 $aAerosols 606 $aInjectors 606 $aChronophotography 606 $aSequence photography 606 $aInjectors$2fast 615 0$aAirplanes$xFuel systems. 615 0$aAerosols. 615 0$aInjectors. 615 0$aChronophotography. 615 0$aSequence photography. 615 7$aInjectors. 700 $aRothrock$b A. M$g(Addison May),$f1903-1971,$01398048 712 02$aUnited States.$bNational Advisory Committee for Aeronautics, 801 0$bOCLCE 801 1$bOCLCE 801 2$bOCLCQ 801 2$bOCLCF 801 2$bCOP 801 2$bGPO 906 $aBOOK 912 $a9910715136103321 996 $aEffect of high air velocities on the distribution and penetration of a fuel spray$93542266 997 $aUNINA LEADER 03241nam 2200457 450 001 9910819512503321 005 20230808204634.0 010 $a3-8325-8795-0 035 $a(CKB)4100000010135383 035 $a(MiAaPQ)EBC6032830 035 $a5e469731-a680-48e9-a7f7-4e00b0dd2d03 035 $a(EXLCZ)994100000010135383 100 $a20200316d2016 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStochastic methods for parameter estimation and design of experiments in systems biology /$fvorgelegt von Andrei Kramer 210 1$aBerlin, Germany :$cLogos Verlag,$d[2016] 210 4$dİ2016 215 $a1 online resource (xii,137 pages) $cillustrations 300 $a"Von der Fakulta?t Konstruktions-, Produktions- und Fahrzeugtechnik der Universita?t Stuttgart zur Erlangung der Wu?rde eines Doktor- Ingenieurs (Dr.-Ing.) genehmigte Abhandlung." 311 $a3-8325-4195-0 320 $aIncludes bibliographical references (pages 127-137). 330 $aLong description: Markov Chain Monte Carlo (MCMC) methods are sampling based techniques, which use random numbers to approximate deterministic but unknown values. They can be used to obtain expected values, estimate parameters or to simply inspect the properties of a non-standard, high dimensional probability distribution. Bayesian analysis of model parameters provides the mathematical foundation for parameter estimation using such probabilistic sampling. The strengths of these stochastic methods are their robustness and relative simplicity even for nonlinear problems with dozens of parameters as well as a built-in uncertainty analysis. Because Bayesian model analysis necessarily involves the notion of prior knowledge, the estimation of unidentifiable parameters can be regularised (by priors) in a straight forward way. This work draws the focus on typical cases in systems biology: relative data, nonlinear ordinary differential equation models and few data points. It also investigates the consequences of parameter estimation from steady state data; consequences such as performance benefits. In biology the data is almost exclusively relative, the raw measurements (e.g. western blot intensities) are normalised by control experiments or a reference value within a series and require the model to do the same when comparing its output to the data. Several sampling algorithms are compared in terms of effective sampling speed and necessary adaptations to relative and steady state data are explained. 606 $aStochastic analysis$xMathematical models 606 $aSystems biology$xStatistical mehods 606 $aBiological systems$xData processing 615 0$aStochastic analysis$xMathematical models. 615 0$aSystems biology$xStatistical mehods. 615 0$aBiological systems$xData processing. 676 $a570.113 700 $aKramer$b Andrei$01661165 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910819512503321 996 $aStochastic methods for parameter estimation and design of experiments in systems biology$94016924 997 $aUNINA