scholarly journals A probabilistic approach to explore signal execution mechanisms with limited experimental data

2019 ◽  
Author(s):  
Michael A. Kochen ◽  
Carlos F. Lopez
Keyword(s):  
Experimental Data ◽  
Probabilistic Approach ◽  
Reaction Network ◽  
Biochemical Network ◽  
Model Parameters ◽  
Type I ◽  
Biochemical Reaction Networks ◽  
Cellular Processes ◽  
Biochemical Systems ◽  
Qualitative Dynamic

AbstractMathematical models of biochemical reaction networks are central to the study of dynamic cellular processes and hypothesis generation that informs experimentation and validation. Unfortunately, model parameters are often not available and sparse experimental data leads to challenges in model calibration and parameter estimation. This can in turn lead to unreliable mechanistic interpretations of experimental data and the generation of poorly conceived hypotheses for experimental validation. To address this challenge, we evaluate whether a Bayesian-inspired probability-based approach, that incorporates available information regarding reaction network topology and parameters, can be used to qualitatively explore hypothetical biochemical network execution mechanisms in the context of limited available data. We test our approach on a model of extrinsic apoptosis execution to identify preferred signal execution modes across varying conditions. Apoptosis signal processing can take place either through a mitochondria independent (Type I) mode or a mitochondria dependent (Type II) mode. We first show that in silico knockouts, represented by model subnetworks, successfully identify the most likely execution mode for specific concentrations of key molecular regulators. We then show that changes in molecular regulator concentrations alter the overall reaction flux through the network by shifting the primary route of signal flow between the direct caspase and mitochondrial pathways. Our work thus demonstrates that probabilistic approaches can be used to explore the qualitative dynamic behavior of model biochemical systems even with missing or sparse data.

scholarly journals Identifiability and Reconstruction of Biochemical Reaction Networks from Population Snapshot Data

Processes ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. 136 ◽  
Author(s):  
Eugenio Cinquemani
Keyword(s):  
Reaction Network ◽  
Network Models ◽  
Stochastic Modelling ◽  
Reaction Rates ◽  
Network Reconstruction ◽  
Biochemical Network ◽  
Biochemical Reaction Networks ◽  
Reconstruction Methods ◽  
Biochemical Interaction ◽  
Reconstruction Performance

Inference of biochemical network models from experimental data is a crucial problem in systems and synthetic biology that includes parameter calibration but also identification of unknown interactions. Stochastic modelling from single-cell data is known to improve identifiability of reaction network parameters for specific systems. However, general results are lacking, and the advantage over deterministic, population-average approaches has not been explored for network reconstruction. In this work, we study identifiability and propose new reconstruction methods for biochemical interaction networks. Focusing on population-snapshot data and networks with reaction rates affine in the state, for parameter estimation, we derive general methods to test structural identifiability and demonstrate them in connection with practical identifiability for a reporter gene in silico case study. In the same framework, we next develop a two-step approach to the reconstruction of unknown networks of interactions. We apply it to compare the achievable network reconstruction performance in a deterministic and a stochastic setting, showing the advantage of the latter, and demonstrate it on population-snapshot data from a simulated example.

scholarly journals Embedded Error Bayesian Calibration of Thermal Decomposition of Organic Materials

2021 ◽  
Author(s):  
Ari L Frankel ◽  
Ellen Wagman ◽  
Ryan Keedy ◽  
Brent C. Houchens ◽  
Sarah Scott
Keyword(s):  
Experimental Data ◽  
Thermogravimetric Analysis ◽  
Structural Integrity ◽  
Organic Materials ◽  
Reaction Network ◽  
Analysis Data ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Kinetics Models ◽  
Model Form

Abstract Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chem- ical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous e?orts in this field have largely been limited to finding a single best-fit set of parame- ters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simul- taneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. The distributions may be used in forward propagation of uncertainty in models that leverage this material.

scholarly journals Statistical-model calculations for α-capture reactions relevant to the p process

2019 ◽  
Vol 26 ◽  
pp. 228
Author(s):  
C. Fakiola ◽  
I. Karakasis ◽  
I. Sideris ◽  
A. Khaliel ◽  
T. J. Mertzimekis
Keyword(s):  
Experimental Data ◽  
Statistical Model ◽  
Cross Sections ◽  
Theoretical Calculations ◽  
Reaction Network ◽  
Reaction Cross ◽  
Model Parameters ◽  
Model Calculations ◽  
Reaction Channels ◽  
Reaction Cross Sections

About 35 nuclides which lie on the neutron deficient side of the isotopic chart cannot be created by the two basic nucleosynthetic processes, the sand the rprocess. Due to scarce experimental data and the vast complexity of the reaction network involved, cross sections and reactions are estimated theoretically, using the Hauser–Feshbach statistical model. In the present work, theoretical calculations of cross sections of radiative α-capture reactions on the neutron–deficient Erbium and Xenon isotopes are presented in an attempt to make predictions inside the astrophysically relevant energy window (Gamow). The particular reactions are predicted to be sensitive branchings in the γprocess path.The most recent versions of TALYS (v1.9) and Fresco codes were employed for all calculations, initially focusing on investigating the influence of the default eight (8) α–nucleus optical potential models of TALYS on reaction cross sections. The theoretical results of both codes are compared and for the reactions where experimental data exist in literature, the optical model parameters were adjusted appropriately to best describe the data and were subsequently used for estimating (α,γ) reaction cross sections. Predictions for the (α,n) reaction channels have also been calculated and studied.

scholarly journals Quantification of Type I Interferon Inhibition by Viral Proteins: Ebola Virus as a Case Study

Viruses ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2441
Author(s):  
Macauley Locke ◽  
Grant Lythe ◽  
Martín López-García ◽  
César Muñoz-Fontela ◽  
Miles Carroll ◽  
...  
Keyword(s):  
Experimental Data ◽  
Immune Responses ◽  
Mathematical Models ◽  
Viral Protein ◽  
Sequential Monte Carlo ◽  
Viral Proteins ◽  
Type I Interferons ◽  
Model Parameters ◽  
Type I ◽  
Type I Ifn

Type I interferons (IFNs) are cytokines with both antiviral properties and protective roles in innate immune responses to viral infection. They induce an antiviral cellular state and link innate and adaptive immune responses. Yet, viruses have evolved different strategies to inhibit such host responses. One of them is the existence of viral proteins which subvert type I IFN responses to allow quick and successful viral replication, thus, sustaining the infection within a host. We propose mathematical models to characterise the intra-cellular mechanisms involved in viral protein antagonism of type I IFN responses, and compare three different molecular inhibition strategies. We study the Ebola viral protein, VP35, with this mathematical approach. Approximate Bayesian computation sequential Monte Carlo, together with experimental data and the mathematical models proposed, are used to perform model calibration, as well as model selection of the different hypotheses considered. Finally, we assess if model parameters are identifiable and discuss how such identifiability can be improved with new experimental data.

scholarly journals Simulating intervertebral disc cell behaviour within 3D multifactorial environments

2020 ◽  
Author(s):  
L Baumgartner ◽  
J J Reagh ◽  
M A González Ballester ◽  
J Noailly
Keyword(s):  
Experimental Data ◽  
Intervertebral Disc ◽  
Cell Viability ◽  
Mrna Expression ◽  
Collagen Type ◽  
Supplementary Information ◽  
Model Parameters ◽  
Type I ◽  
Cell Behaviour ◽  
Model Predictions

Abstract Motivation Low back pain is responsible for more global disability than any other condition. Its incidence is closely related to intervertebral disc (IVD) failure, which is likely caused by an accumulation of microtrauma within the IVD. Crucial factors in microtrauma development are not entirely known yet, probably because their exploration in vivo or in vitro remains tremendously challenging. In silico modelling is, therefore, definitively appealing, and shall include approaches to integrate influences of multiple cell stimuli at the microscale. Accordingly, this study introduces a hybrid Agent-based (AB) model in IVD research and exploits network modelling solutions in systems biology to mimic the cellular behaviour of Nucleus Pulposus cells exposed to a 3D multifactorial biochemical environment, based on mathematical integrations of existing experimental knowledge. Cellular activity reflected by mRNA expression of Aggrecan, Collagen type I, Collagen type II, MMP-3 and ADAMTS were calculated for inflamed and non-inflamed cells. mRNA expression over long periods of time is additionally determined including cell viability estimations. Model predictions were eventually validated with independent experimental data. Results As it combines experimental data to simulate cell behaviour exposed to a multifactorial environment, the present methodology was able to reproduce cell death within 3 days under glucose deprivation and a 50% decrease in cell viability after 7 days in an acidic environment. Cellular mRNA expression under non-inflamed conditions simulated a quantifiable catabolic shift under an adverse cell environment, and model predictions of mRNA expression of inflamed cells provide new explanation possibilities for unexpected results achieved in experimental research. Availabilityand implementation The AB model as well as used mathematical functions were built with open source software. Final functions implemented in the AB model and complete AB model parameters are provided as Supplementary Material. Experimental input and validation data were provided through referenced, published papers. The code corresponding to the model can be shared upon request and shall be reused after proper training. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Parameter Determination for Chloride and Tritium Transport in Undisturbed Lysimeters during Steady Flow

1992 ◽  
Vol 23 (2) ◽  
pp. 89-104 ◽  
Author(s):  
Ole H. Jacobsen ◽  
Feike J. Leij ◽  
Martinus Th. van Genuchten
Keyword(s):  
Experimental Data ◽  
Unsaturated Flow ◽  
Transport Model ◽  
Time Moment ◽  
Breakthrough Curves ◽  
Coarse Sand ◽  
Retardation Factor ◽  
Parameter Determination ◽  
Model Parameters ◽  
Water Fraction

Breakthrough curves of Cl and 3H2O were obtained during steady unsaturated flow in five lysimeters containing an undisturbed coarse sand (Orthic Haplohumod). The experimental data were analyzed in terms of the classical two-parameter convection-dispersion equation and a four-parameter two-region type physical nonequilibrium solute transport model. Model parameters were obtained by both curve fitting and time moment analysis. The four-parameter model provided a much better fit to the data for three soil columns, but performed only slightly better for the two remaining columns. The retardation factor for Cl was about 10 % less than for 3H2O, indicating some anion exclusion. For the four-parameter model the average immobile water fraction was 0.14 and the Peclet numbers of the mobile region varied between 50 and 200. Time moments analysis proved to be a useful tool for quantifying the break through curve (BTC) although the moments were found to be sensitive to experimental scattering in the measured data at larger times. Also, fitted parameters described the experimental data better than moment generated parameter values.

Comparative analysis and verification of engineering methods of shallow cracks effect for fracture toughness prediction for reactor pressure vessels

2020 ◽  
pp. 140-165
Author(s):  
V. I. Kostylev ◽  
B. Z. Margolin
Keyword(s):  
Experimental Data ◽  
Fracture Toughness ◽  
Comparative Analysis ◽  
Nuclear Reactor ◽  
Probabilistic Approach ◽  
Pressure Vessels ◽  
Local Methods ◽  
European Method ◽  
Shallow Crack ◽  
Reactor Pressure

The main features of shallow cracks fracture are considered, and a brief analysis of methods allowing to predict the temperature dependence of the fracture toughness KJC (T) for specimens with shallow cracks is given. These methods include DA-method, (JQ)-method, (J-T)-method, “local methods” with its multiparameter probabilistic approach, GP method uses power approach, and also two engineering methods – RMSC (Russian Method for Shallow Crack) and EMSC (European Method for Shallow Crack). On the basis of 13 sets of experimental data for national and foreign steels, a detailed verification and comparative analysis of these two engineering methods were carried out on the materials of the VVER and PWR nuclear reactor vessels considering the effect of shallow cracks.

scholarly journals Modelling the Inflation and Elastic Instabilities of Rubber-Like Spherical and Cylindrical Shells Using a New Generalised Neo-Hookean Strain Energy Function

2021 ◽  
Author(s):  
Afshin Anssari-Benam ◽  
Andrea Bucchi ◽  
Giuseppe Saccomandi
Keyword(s):  
Experimental Data ◽  
Energy Function ◽  
Limit Point ◽  
Strain Energy ◽  
Cylindrical Shells ◽  
Strain Energy Function ◽  
Model Parameters ◽  
Wide Range ◽  
Cylindrical Tubes ◽  
Gent Model

AbstractThe application of a newly proposed generalised neo-Hookean strain energy function to the inflation of incompressible rubber-like spherical and cylindrical shells is demonstrated in this paper. The pressure ($P$ P ) – inflation ($\lambda $ λ or $v$ v ) relationships are derived and presented for four shells: thin- and thick-walled spherical balloons, and thin- and thick-walled cylindrical tubes. Characteristics of the inflation curves predicted by the model for the four considered shells are analysed and the critical values of the model parameters for exhibiting the limit-point instability are established. The application of the model to extant experimental datasets procured from studies across 19th to 21st century will be demonstrated, showing favourable agreement between the model and the experimental data. The capability of the model to capture the two characteristic instability phenomena in the inflation of rubber-like materials, namely the limit-point and inflation-jump instabilities, will be made evident from both the theoretical analysis and curve-fitting approaches presented in this study. A comparison with the predictions of the Gent model for the considered data is also demonstrated and is shown that our presented model provides improved fits. Given the simplicity of the model, its ability to fit a wide range of experimental data and capture both limit-point and inflation-jump instabilities, we propose the application of our model to the inflation of rubber-like materials.

A Theoretical Analysis of CO2 Absorption in Sun Versus Shade Leaves

1978 ◽  
Vol 100 (1) ◽  
pp. 20-24 ◽  
Author(s):  
R. H. Rand
Keyword(s):  
Experimental Data ◽  
Quantitative Estimate ◽  
Geometric Model ◽  
Model Parameters ◽  
Co2 Absorption ◽  
Temperature Model ◽  
Spongy Mesophyll ◽  
One Dimensional ◽  
Mesophyll Tissue ◽  
Shade Leaves

A one-dimensional, steady-state, constant temperature model of diffusion and absorption of CO2 in the intercellular air spaces of a leaf is presented. The model includes two geometrically distinct regions of the leaf interior, corresponding to palisade and spongy mesophyll tissue, respectively. Sun, shade, and intermediate light leaves are modeled by varying the thicknesses of these two regions. Values of the geometric model parameters are obtained by comparing geometric properties of the model with experimental data of other investigators found from dissection of real leaves. The model provides a quantitative estimate of the extent to which the concentration of gaseous CO2 varies locally within the leaf interior.

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