scholarly journals On-Line Optimal Input Design Increases the Efficiency and Accuracy of the Modelling of an Inducible Synthetic Promoter

Processes ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. 148 ◽  
Author(s):  
Lucia Bandiera ◽  
Zhaozheng Hou ◽  
Varun Kothamachu ◽  
Eva Balsa-Canto ◽  
Peter Swain ◽  
...  
Keyword(s):  
Experimental Design ◽  
A Priori ◽  
Inducible Promoter ◽  
Optimal Experimental Design ◽  
Parameter Inference ◽  
Synthetic Gene Circuits ◽  
Input Design ◽  
On Line

Synthetic biology seeks to design biological parts and circuits that implement new functions in cells. Major accomplishments have been reported in this field, yet predicting a priori the in vivo behaviour of synthetic gene circuits is major a challenge. Mathematical models offer a means to address this bottleneck. However, in biology, modelling is perceived as an expensive, time-consuming task. Indeed, the quality of predictions depends on the accuracy of parameters, which are traditionally inferred from poorly informative data. How much can parameter accuracy be improved by using model-based optimal experimental design (MBOED)? To tackle this question, we considered an inducible promoter in the yeast S. cerevisiae. Using in vivo data, we re-fit a dynamic model for this component and then compared the performance of standard (e.g., step inputs) and optimally designed experiments for parameter inference. We found that MBOED improves the quality of model calibration by ∼60%. Results further improve up to 84 % when considering on-line optimal experimental design (OED). Our in silico results suggest that MBOED provides a significant advantage in the identification of models of biological parts and should thus be integrated into their characterisation.

OPTIMAL EXPERIMENTAL DESIGN FOR STRUCTURE CHARACTERIZATION OF BIODEGRADATION MODELS: ON-LINE IMPLEMENTATION IN A RESPIROGRAPHIC BIOSENSOR

1994 ◽  
Vol 30 (4) ◽  
pp. 243-253 ◽  
Author(s):  
P. Vanrolleghem ◽  
M. Van Daele
Keyword(s):  
Experimental Design ◽  
A Priori ◽  
Treatment Plant ◽  
Model Identification ◽  
Structure Characterization ◽  
Optimal Experimental Design ◽  
Process Conditions ◽  
Model Structure ◽  
Characterization Methods ◽  
On Line

The interaction between activated sludge and a wastewater is subject to important cbanges. This is reflected not only in changing biokinetic parameters but also in changing model structures. The need to select the ‘ right’ model structure in a reliable way on the basis of respirographic data provided by on-line sensors imposes serious real-time constraints on the methods used. First of all, fast structure characterization methods are presented allowing us to track the model structure on-line. Since these so-called a priori methods are less computing intensive, they can be at the basis of optimal experimental design calculations that can be performed on-line. This allows us to maintain the quality of the overall model identification under the changing process conditions of a wastewater treatment plant. Two applications of Optimal Experimental Design are given.

scholarly journals Phylogenetic Synecdoche Demonstrates Optimality of Subsampling and Improves Recovery of the Blaberoidea Phylogeny

2019 ◽  
Author(s):  
Dominic A. Evangelista ◽  
Sabrina Simon ◽  
Megan M. Wilson ◽  
Akito Y. Kawahara ◽  
Manpreet K. Kohli ◽  
...  
Keyword(s):  
Experimental Design ◽  
Information Content ◽  
Mutation Rate ◽  
A Priori ◽  
Computation Time ◽  
Evolutionary Divergence ◽  
Rate Heterogeneity ◽  
Tree Inference ◽  
Dataset Size

AbstractPhylogenomics seeks to use next-generation data to robustly infer an organism’s evolutionary history. Yet, the practical caveats of phylogenomics motivates investigation of improved efficiency, particularly when quality of phylogenies are questionable. To achieve improvements, one goal is to maintain or enhance the quality of phylogenetic inference while severely reducing dataset size. We approach this goal by designing an optimized subsample of data with an experimental design whose results are determined on the basis of phylogenetic synecdoche − a comparison of phylogenies inferred from a subsample to phylogenies inferred from the entire dataset. We examine locus mutation rate, saturation, evolutionary divergence, rate heterogeneity, selection, and a priori information content as traits that may determine optimality. Our controlled experimental design is based on 265 loci for 102 blaberoidean cockroaches and 22 outgroup species. High phylogenetic utility is demonstrated by loci with high mutation rate, low saturation, low sequence distance, low rate heterogeneity, and low selection. We found that some phylogenetic information content estimators may not be meaningful for assessing information content a priori. We use these findings to design concatenated datasets with an optimized subsample of 100 loci. The tree inferred from the optimized subsample alignment was largely identical to that inferred from all 265 loci but with less evidence of long branch attraction and improved statistical support. In sum, optimized subsampling can improve tree quality while reducing data collection costs and yielding 4-6x improvements to computation time in tree inference and bootstrapping.

A scalable method for parameter identification in kinetic models of metabolism using steady-state data

2019 ◽  
Vol 35 (24) ◽  
pp. 5216-5225 ◽  
Author(s):  
Shyam Srinivasan ◽  
William R Cluett ◽  
Radhakrishnan Mahadevan
Keyword(s):  
Steady State ◽  
Experimental Design ◽  
Kinetic Models ◽  
Metabolic Networks ◽  
Enzyme Level ◽  
A Priori ◽  
Supplementary Information ◽  
State Data ◽  
Rate Laws

Abstract Motivation In kinetic models of metabolism, the parameter values determine the dynamic behaviour predicted by these models. Estimating parameters from in vivo experimental data require the parameters to be structurally identifiable, and the data to be informative enough to estimate these parameters. Existing methods to determine the structural identifiability of parameters in kinetic models of metabolism can only be applied to models of small metabolic networks due to their computational complexity. Additionally, a priori experimental design, a necessity to obtain informative data for parameter estimation, also does not account for using steady-state data to estimate parameters in kinetic models. Results Here, we present a scalable methodology to structurally identify parameters for each flux in a kinetic model of metabolism based on the availability of steady-state data. In doing so, we also address the issue of determining the number and nature of experiments for generating steady-state data to estimate these parameters. By using a small metabolic network as an example, we show that most parameters in fluxes expressed by mechanistic enzyme kinetic rate laws can be identified using steady-state data, and the steady-state data required for their estimation can be obtained from selective experiments involving both substrate and enzyme level perturbations. The methodology can be used in combination with other identifiability and experimental design algorithms that use dynamic data to determine the most informative experiments requiring the least resources to perform. Availability and implementation https://github.com/LMSE/ident. Supplementary information Supplementary data are available at Bioinformatics online

Sound recording and digital phonocardiography of cardiac murmurs in dogs by using a sensor-based electronic stethoscope

2011 ◽  
Vol 59 (1) ◽  
pp. 23-35 ◽  
Author(s):  
Károly Vörös ◽  
Ingo Nolte ◽  
Stephan Hungerbühler ◽  
Jenő Reiczigel ◽  
Jan Ehlers ◽  
...  
Keyword(s):  
Correlation Coefficients ◽  
Weighted Kappa ◽  
Sound Recording ◽  
Sound Recordings ◽  
Electronic Stethoscope ◽  
Additional Tool ◽  
On Line ◽  
Diagnostic Capabilities

The goals of this study were to present a technique of digitalised sound recordings and phonocardiograms (dPCGs), and to analyse its diagnostic capabilities. Heart sounds of 20 dogs were auscultated in vivo (on-line) and recorded with dPCGs by two authors using a Welch Allyn Meditron Stethoscope System. Sound recordings were auscultated off-line and blindly by four different observers having various auscultatory experiences, then listened to while viewing dPCGs. The results were compared to echocardiographic diagnoses. There was a significant agreement (p < 0.001) between on-line and off-line auscultatory findings regarding the four observers, ranging from 45% to 75% (weighted kappa values: 0.72 to 0.87). The best agreement was achieved by Observer 1 having the highest experience. Significant differences (p < 0.05) were found between Observer 1 and Observer 4 (with the lowest experience) in judging the quality of the murmurs during the off-line and blind auscultation. However, there were only minimal differences (95% to 100% agreements) in dPCG analyses among the four observers regarding intensity and quality of the murmurs while simultaneously listening to and viewing the dPCGs. Significant correlations were found between the traditional ‘0 to 6 scale’ and a new ‘0 to 3 scale’ murmur intensity gradings by all observers (correlation coefficients 0.640 to 0.908; p < 0.01 to p < 0.001). Analysis of dPCGs might be a valuable, additional tool helping with the diagnosis of canine cardiac murmurs, especially for those with less cardiological experience.

scholarly journals Formulation Optimization Utilizing D-Optimal Experimental Design of Oral Capsules Containing Enteric-Coated Pellets of Lansoprazole and<i> in vivo </i>Bioequivalence

2017 ◽  
Vol 08 (05) ◽  
pp. 153-171
Author(s):  
Anh Quang Luong ◽  
Thang Ngoc Vu ◽  
Dang Hoa Nguyen ◽  
Sultan M. Alshahrani ◽  
John Mark Christensen ◽  
...  
Keyword(s):  
Experimental Design ◽  
Optimal Experimental Design ◽  
Formulation Optimization ◽  
Enteric Coated
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