scholarly journals Phenotype-Centric Modeling for Rational Metabolic Engineering

2021 ◽  
Author(s):  
Miguel Angel Valderrama-Gomez ◽  
Michael A. Savageau
Keyword(s):  
Metabolic Engineering ◽  
Paradigm Shift ◽  
Design Space ◽  
Global Analysis ◽  
A Priori ◽  
Computationally Intensive ◽  
Modeling Strategy ◽  
Parameter Values ◽  
Intensive Parameter

Phenotype-centric modeling enables a paradigm shift in the analysis of kinetic models. It brings the focus to a network's biochemical phenotypes and their relationship with measurable traits (e.g., product yields, system dynamics, signal amplification factors, etc.) and away from computationally intensive parameter sampling and numerical simulation. Here, we explore applications of this new modeling strategy in the field of Rational Metabolic Engineering using the amorphadiene biosynthetic network as a case study. Our phenotype-centric approach not only identifies known beneficial intervention strategies for this network, but it also provides an understanding of the mechanistic context for the validity of these predictions. Additionally, we propose a set of hypothetical strains with the potential to outperform reported production strains and enhance the mechanistic understanding of the amorphadiene biosynthetic network. We believe that phenotype-centric modeling can advance the field of Rational Metabolic Engineering by enabling the development of next generation kinetics-based algorithms and methods that do not rely on a priori knowledge of kinetic parameters but allow a structured, global analysis of the design space of parameter values.

scholarly journals Mechanistic Modeling of Biochemical Systems Without A Priori Parameter Values Using the Design Space Toolbox v.3.0

2020 ◽  
Author(s):  
Miguel Á. Valderrama-Gómez ◽  
Jason G. Lomnitz ◽  
Rick A. Fasani ◽  
Michael A. Savageau
Keyword(s):  
Design Space ◽  
A Priori ◽  
Design Principles ◽  
Mechanistic Modeling ◽  
Design And Optimization ◽  
Biological Design ◽  
Biological Phenomena ◽  
Biochemical Systems ◽  
Space Formalism ◽  
Parameter Values

SummaryMechanistic models of biochemical systems provide a rigorous kinetics-based description of various biological phenomena. They are indispensable to elucidate biological design principles and to devise and engineer systems with novel functionalities. To date, mathematical analysis and characterization of these models remain a challenging endeavor, the main difficulty being the lack of information for most system parameters. Here, we introduce the Design Space Toolbox v.3.0 (DST3), a software implementation of the Design Space formalism that enables mechanistic modeling of complex biological processes without requiring previous knowledge of the parameter values involved. This is achieved by making use of a phenotype-centric modeling approach, in which the system is first decomposed into a series of biochemical phenotypes. Parameter values realizing phenotypes of interest are predicted in a second step. DST3 represents the most generally applicable implementation of the Design Space formalism to date and offers unique advantages over earlier versions. By expanding the capabilities of the Design Space formalism and streamlining its distribution, DST3 represents a valuable tool for elucidating biological design principles and guiding the design and optimization of novel synthetic circuits.

scholarly journals Mechanistic Modeling of Biochemical Systems without A Priori Parameter Values Using the Design Space Toolbox v.3.0

iScience ◽  
2020 ◽  
Vol 23 (6) ◽  
pp. 101200 ◽  
Author(s):  
Miguel Á. Valderrama-Gómez ◽  
Jason G. Lomnitz ◽  
Rick A. Fasani ◽  
Michael A. Savageau
Keyword(s):  
Design Space ◽  
A Priori ◽  
Mechanistic Modeling ◽  
Biochemical Systems ◽  
Parameter Values

scholarly journals Decision-Making Processes in Controlling Exposure to Sunlight Supported by Simulation Tools: A Case Study in Warm Weather

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4100
Author(s):  
Mariana Huskinson ◽  
Antonio Galiano-Garrigós ◽  
Ángel Benigno González-Avilés ◽  
M. Isabel Pérez-Millán
Keyword(s):  
Decision Making ◽  
Global Analysis ◽  
Energy Performance ◽  
Information Modeling ◽  
The European Union ◽  
Evaluation Tool ◽  
Simulation Tools ◽  
Building Information ◽  
The Impact

Improving the energy performance of existing buildings is one of the main strategies defined by the European Union to reduce global energy costs. Amongst the actions to be carried out in buildings to achieve this objective is working with passive measures adapted to each type of climate. To assist designers in the process of finding appropriate solutions for each building and location, different tools have been developed and since the implementation of building information modeling (BIM), it has been possible to perform an analysis of a building’s life cycle from an energy perspective and other types of analysis such as a comfort analysis. In the case of Spain, the first BIM environment tool has been implemented that deals with the global analysis of a building’s behavior and serves as an alternative to previous methods characterized by their lack of both flexibility and information offered to designers. This paper evaluates and compares the official Spanish energy performance evaluation tool (Cypetherm) released in 2018 using a case study involving the installation of sunlight control devices as part of a building refurbishment. It is intended to determine how databases and simplifications affect the designer’s decision-making. Additionally, the yielded energy results are complemented by a comfort analysis to explore the impact of these improvements from a users’ wellbeing viewpoint. At the end of the process the yielded results still confirm that the simulation remains far from reality and that simulation tools can indeed influence the decision-making process.

scholarly journals A Fast Estimator for Binary Choice Models with Spatial, Temporal, and Spatio-Temporal Interdependence

2021 ◽  
pp. 1-7
Author(s):  
Julian Wucherpfennig ◽  
Aya Kachi ◽  
Nils-Christian Bormann ◽  
Philipp Hunziker
Keyword(s):  
Computational Cost ◽  
Choice Models ◽  
Reduced Form ◽  
Binary Choice ◽  
Monte Carlo Experiments ◽  
Binary Choice Models ◽  
Spatio Temporal ◽  
Computationally Intensive ◽  
Pseudo Maximum Likelihood ◽  
Parameter Values

Abstract Binary outcome models are frequently used in the social sciences and economics. However, such models are difficult to estimate with interdependent data structures, including spatial, temporal, and spatio-temporal autocorrelation because jointly determined error terms in the reduced-form specification are generally analytically intractable. To deal with this problem, simulation-based approaches have been proposed. However, these approaches (i) are computationally intensive and impractical for sizable datasets commonly used in contemporary research, and (ii) rarely address temporal interdependence. As a way forward, we demonstrate how to reduce the computational burden significantly by (i) introducing analytically-tractable pseudo maximum likelihood estimators for latent binary choice models that exhibit interdependence across space and time and by (ii) proposing an implementation strategy that increases computational efficiency considerably. Monte Carlo experiments show that our estimators recover the parameter values as good as commonly used estimation alternatives and require only a fraction of the computational cost.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

scholarly journals AN INVESTIGATION ON THE IMPROVEMENT OF CONSTRUCTION EXPENDITURE FORECASTING

2013 ◽  
Vol 19 (5) ◽  
pp. 759-711 ◽  
Author(s):  
Andrew Ross ◽  
Katie Dalton ◽  
Begum Sertyesilisik
Keyword(s):  
Cash Flow ◽  
Construction Projects ◽  
Case Study Research ◽  
Research Strategy ◽  
Flow Models ◽  
Improved Model ◽  
Work Affect ◽  
Cash Flow Forecast ◽  
Parameter Values

This study aims to determine the accuracy of the cash flow models and to investigate if these models could be more accurate if they accounted for the potentially influential variables specific to individual construction projects. An analytical case study research strategy has been implemented in collecting data for the construction projects. The data collected has been tested against recognised models. Statistical analyses have been carried out on the data for the specified variables, culminating in the potential proposal of an improved model with respect to these identified variables. The results revealed that the independent variables (type of construction, procurement route and type of work) affect the cash flow forecast. The findings suggested that a model could be more accurate with the input of more job-specific variables and that Hudson's DHSS model is best suited to a construction project procured traditionally. Adopting the ‘trial and error’ approach, Hudson's DHSS model has been recognised as an accurate model that could be adapted slightly, through changing the parameter values. The clients and the contractors are the main beneficiaries approached for this study.

Adaptive Geometry Representation of Turbine Vane Frames for Use in Optimization

2021 ◽  
Author(s):  
Sebastian F. Riebl ◽  
Christian Wakelam ◽  
Reinhard Niehuis
Keyword(s):  
Design Space ◽  
Cfd Simulation ◽  
A Priori ◽  
Three Dimensional ◽  
Optimization Method ◽  
Three Dimensions ◽  
Design Parameters ◽  
Adjustment Process ◽  
Turbine Vane ◽  
Integrated Concept

Abstract Turbine Vane Frames (TVF) are a way to realize more compact jet engine designs. Located between the high pressure turbine (HPT) and the low pressure turbine (LPT), they fulfill structural and aerodynamic tasks. When used as an integrated concept with splitters located between the structural load-bearing vanes, the TVF configuration contains more than one type of airfoil with sometimes pronouncedly different properties. This system of multidisciplinary demands and mixed blading poses an interesting opportunity for optimization. Within the scope of the present work, a full geometric parameterization of a TVF with splitters is presented. The parameterization is chosen as to minimize the number of parameters required to automatically and flexibly represent all blade types involved in a TVF row in all three dimensions. Typical blade design parameters are linked to the fourth order Bézier-curve controlled camber line-thickness parameterization. Based on conventional design rules, a procedure is presented, which sets the parameters within their permissible ranges according to the imposed constraints, using a proprietary developed code. The presented workflow relies on subsequent three dimensional geometry generation by transfer of the proposed parameter set to a commercially available CAD package. The interdependencies of parameters are discussed and their respective significance for the adjustment process is detailed. Furthermore, the capability of the chosen parameterization and adjustment process to rebuild an exemplary reference TVF geometry is demonstrated. The results are verified by comparing not only geometrical profile data, but also validated CFD simulation results between the rebuilt and original geometries. Measures taken to ensure the robustness of the method are highlighted and evaluated by exploring extremes in the permissible design space. Finally, the embedding of the proposed method within the framework of an automated, gradient free numerical optimization is discussed. Herein, implications of the proposed method on response surface modeling in combination with the optimization method are highlighted. The method promises to be an option for improvement of optimization efficiency in gradient free optimization of interdependent blade geometries, by a-priori excluding unsuitable blade combinations, yet keeping restrictions to the design space as limited as possible.

Enabling Decision-Based Design Using Solution Trajectory Correction and Backtracking Rules

2012 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Zissimos P. Mourelatos ◽  
Monica Majcher
Keyword(s):  
Optimal Design ◽  
Utility Function ◽  
Design Space ◽  
A Priori ◽  
Preference Order ◽  
Beam Design ◽  
Effective Decision ◽  
Suboptimal Design ◽  
Trajectory Correction ◽  
Decision Based Design

Optimization is needed for effective decision based design (DBD). However, a utility function assessed a priori in DBD does not usually capture the preferences of the decision maker over the entire design space. As a result, when the optimizer searches for the optimal design, it traverses (or ends up) in regions where the preference order among different solutions is different from the actual order. For a highly non-convex design space, this can lead to convergence to a grossly suboptimal design depending on the initial design. In this article, we propose two approaches to alleviate this issue. First, we map the trajectory of the solution as generated by the optimizer and generate ranking questions that are presented to the designer to verify the correctness of the utility function. We then propose backtracking rules if a local utility function is very different from the initially assessed function. We demonstrate our methodology using a mathematical example and a welded beam design problem.

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