, InChI=1S/C7H6O2, pp.8-15

, h1-5H,6H2,(H,10,13)(H,11,12) 3. Cocaine: InChI=1S/C17H21NO4/c1, InChI=1S/C9H9NO3, pp.6-10

, Selenzyme results for EC 1.1.1

. .. , Number of generated alkane isomers by canonical augmentation algorithm and isomer transformation algorithm, p.56

, List of the 19 SMARTS rules that were used in this study, p.78

. .. , Solution space reduction arguments or rules, p.79

. .. , Average branching factor for chosen sets, p.85

. .. , Average branching factor for individual diameters, vol.104

. .. Toxicity-biased-results,

. .. Golden, , p.107

. .. , Detectable compounds dataset specifications, p.119

, Detectable compounds data sources

. .. , Sequence of the plasmid used in this study, p.141

. .. Successful-biosensors, , p.156

. .. Pinocembrin, , p.167

. .. , Parameters for the time-course model, p.168

.. .. Biosensors,

. .. Flavonoids-similarity-to-pinocembrin, , p.182

. .. Strains, , p.183

. .. Primers, , p.183

, Copy numbers of the used plasmids for pinocembrin biosensor, vol.184

. .. Pinocembrin-sensor-constructs-list, , p.185

, Deterministic models developed to understand cell-free, p.193

, Number of RNAP/ ribosomes per DNA/ mRNA strand, p.227

, Effective translation rates in vivo and in cell-free, p.227

.. .. Enzymes'-catalytic-constants,

. .. , Numerical parameters used during simulations, p.229

, Fluorescence results from calibration of TF and reporter plasmids, p.239

. .. -ms, Benzoate concentration in commercial beverages determined from three replicates of our cell-free biosensor and LC, p.240

. .. , Benzoic acid sensor shows minimal activation in response to human urine without HipO metabolic transducer, p.240

, Fluorescence results from calibration of HipO and CocE metabolic transducer plasmids, p.295

. .. -ms, Endogenous hippuric acid concentration in human urine samples determined from three replicates of our cell-free biosensor and LC

. .. , 268 10.2 Sequences identifiers for parts used in this work, p.284

. .. , Parameter estimations for in vivo model, p.285

, One-step method to predict protein yield in cell-free systems, p.131

, Preliminary calibration of the cell-free composition, p.140

, The choice of 102 cell-free compositions for training and testing of our model

, Mutual information analysis

, Global comparison between the yields obtained with different lysates 142

, Comparison between the behavior of the local yields measured with different lysates and the yields measured with the lysate ORI, p.142

, A decrease in ribosome availability is sufficient to explain the saturation of the yields with Lysate Spectinomycin, p.143

. .. , Absolute measurements in cell-free reaction, p.144

. .. , , p.152

, Different strategies to develop a TF based biosensor for a given metabolite

. .. Pinocembrin-cell-free-biosensor, , p.159

. .. Pinocembrin-biosynthesis-pathway, , p.164

. .. Pinocembrin-biosensor-module, , p.165

, Dose responses of different biosensor constructs, p.171

. .. , Effect of copy number variations of fold change, p.172

, Model fitting of pinocembrin data

, Model fitting of naringenin data -no correction, p.176

, Model fitting of naringenin data

, Copy number model predictions

. .. , 186 7.10 Growth model fitting to construct 357

, Growth rate of constructs with varying resistance markers, p.188

. .. , , p.190

. .. , , p.190

, 194 8.2 Resource competition in cell-free

, A modular design workflow for engineering scalable cell-free biosensors

, Calibration of sensor and output modules for benzoate detection, p.203

, Modeling titration of transcription factor and reporter plasmids, vol.204

, Expanding the chemical detection space of cell-free biosensors by plugging various metabolic transducers into an optimized sensor module

, Detecting benzoic acid, hippuric acid, and cocaine in complex samples

, Modeling metabolic transducer behavior for HipO and CocE, p.217

, Superfolder-GFP expression with J23101 and pBEST promoter (OR2-OR1-Pr)

. .. , Model-predicted shift in HipO concentration for peak biosensor signal at high concentrations of TF plasmid and inducer, p.219

, Time course of the benzoic acid biosensor response to varying concentrations of inducer

, Time course of the hippuric acid biosensor response to varying concentrations of inducer

, Time course of the cocaine biosensor response to varying concentrations of inducer

, Time course of the benzoic biosensor response to 1x and 0.1x bev

, Interference of 0.1x and 1x beverages on cell-free reaction with constitutive sfGFP plasmid

, Hill plot fit of a standard gradient of benzoic acid to calibrate sensor, p.234

, Hill plot fit of a standard gradient of hippuric acid to calibrate sensor, p.235

, Correlation between cell-free biosensor and LC-MS measurements of endogenous hippuric acid levels in human urine, p.235

, Detection of cocaine spiked into clinical urine samples with sfGFP output module

. .. , Cell-free reactions accumulate autofluorescent products in the GFP channel even in the absence of DNA, p.236

, Use of firefly luciferase as an output module enhances benzoic acid sensor fold change

, Comparison of benzoic acid and cocaine biosensor expression in response to urinary cocaine gradient

. .. , , p.247

, Whole-cell metabolic adder of hippurate and benzaldehyde, p.249

-. .. Cell, , p.251

, Cell-free weighted transducers characterized by varying the concentration of the enzyme DNA

.. .. Cell-free-adder,

, 258 10.7 Feedback-loop circuit design of the benzoate actuator, p.270

, 270 10.9 2D plots for the data presented in heat-map in Figure 10.2b . . . 271 10.10 Examining the effect of resource competition versus enzyme efficiency on the whole-cell cocaine transducer, p.272

. .. , Examining the effect of resource competition versus enzyme efficiency on the whole-cell metabolic adder, p.272

, The specific growth rate (µ) values of the whole-cell circuits presented in Figure 10

, The specific growth rate (µ) values of the whole-cell adder presented in Figure 10

, The dose-response of cell-free transducers to different concentrations of the associated enzyme DNA (weights) for weighted transducers. 275 10.15 Weighted transducers model results

. .. , Five different binary classification problems using a metabolic perceptron for hippurate and cocaine

. .. Hippurate, 280 10.21 Simulations from the random sampling of estimated parameters in whole-cell system, Exploring Hippurate-Cocaine ON-OFF behavior with different weights and input concentrations for

, Simulations from the random sampling of estimated parameters in the cell-free system

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