FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890366991> ?p ?o ?g. }

• W2890366991 abstract "Synthetic biology may be defined as an attempt at using engineering principles to design and build novel biological functionalities. An important class of such functionalities involves the bottom up design of genetic networks (or 'circuits') to control cellular behavior. Performing design iterations on these circuits in vivo is often a time consuming process. One approach that has been developed to address these long design times is to use E. coli cell extracts as simplified circuit prototyping environments. The analogy with similar approaches in engineering, such as prototyping using wind tunnels and breadboards, may be extended by developing accompanying computer aided design tools. In this thesis, we discuss the development of computational and mathematical tools to accelerate circuit prototyping in the TX-TL cell free prototyping platform, and demonstrate some applications of these tools. We start by discussing the problem of reducing circuit behavior variability between different batches of TX-TL cell extracts. To this end, we demonstrate a model-based methodology for calibrating extract batches, and for using the calibrations to 'correct' the behavior of genetic circuits between batches. We also look at the interaction of this methodology with the phenomenon of parameter non-identifiability, which occurs when the parameter identification inverse problem has multiple solutions. In particular, we derive conditions under which parameter non-identifiability does not hinder our modeling objectives, and subsequently demonstrate the use of such non-identifiable models in performing data variability reduction. Next, we describe txtlsim, a MATLAB Simbiology based toolbox for automatically generating models of genetic circuits in TX-TL, and for using these models for part characterization and circuit behavior prediction. Large genetic circuits can have non-negligible resource usage needs, leading to unintended interactions between circuit nodes arising due to the loading of cellular machinery, transcription factors or other regulatory elements. The usage of consumable resources like nucleotides and amino acids can also have non-trivial effects on complex genetic circuits. These types of effects are handled by the modeling framework of txtlsim in a natural way. We also highlight mcmc-simbio, a smaller toolbox within txtlsim for performing concurrent Bayesian parameter inference on Simbiology models. Concurrent inference here means that a common set of parameters can be identified using data from an ensemble of different circuits and experiments, with each experiment informing a subset of the parameters. The combination of the concurrence feature with the fact that Markov chain Monte Carlo based Bayesian inference methods allow for the direct visualization of parameter non-identifiability enables the design of ensembles of experiments that reduce such non-identifiability. Finally, we end with a method for performing model order reduction on transcription and translation elongation models while maintaining the ability of these models to track resource consumption. We show that due to their network topology, our models cannot be brought into the two-timescale form of singular perturbation theory when written in species concentration coordinates. We identify a coordinate system in which singular perturbation theory may be applied to chemical reaction networks more naturally, and use this to achieve the desired model reduction." @default.
• W2890366991 created "2018-09-27" @default.
• W2890366991 creator A5068601494 @default.
• W2890366991 date "2019-01-01" @default.
• W2890366991 modified "2023-09-27" @default.
• W2890366991 title "Modeling, Computation, and Characterization to Accelerate the Development of Synthetic Gene Circuits in Cell-Free Extracts" @default.
• W2890366991 doi "https://doi.org/10.7907/g31j-ch52." @default.
• W2890366991 hasPublicationYear "2019" @default.
• W2890366991 type Work @default.
• W2890366991 sameAs 2890366991 @default.
• W2890366991 citedByCount "0" @default.
• W2890366991 crossrefType "dissertation" @default.
• W2890366991 hasAuthorship W2890366991A5068601494 @default.
• W2890366991 hasConcept C111919701 @default.
• W2890366991 hasConcept C113775141 @default.
• W2890366991 hasConcept C119599485 @default.
• W2890366991 hasConcept C119857082 @default.
• W2890366991 hasConcept C122770356 @default.
• W2890366991 hasConcept C127413603 @default.
• W2890366991 hasConcept C133731056 @default.
• W2890366991 hasConcept C134146338 @default.
• W2890366991 hasConcept C191908910 @default.
• W2890366991 hasConcept C24326235 @default.
• W2890366991 hasConcept C2780365114 @default.
• W2890366991 hasConcept C41008148 @default.
• W2890366991 hasConcept C60644358 @default.
• W2890366991 hasConcept C86803240 @default.
• W2890366991 hasConceptScore W2890366991C111919701 @default.
• W2890366991 hasConceptScore W2890366991C113775141 @default.
• W2890366991 hasConceptScore W2890366991C119599485 @default.
• W2890366991 hasConceptScore W2890366991C119857082 @default.
• W2890366991 hasConceptScore W2890366991C122770356 @default.
• W2890366991 hasConceptScore W2890366991C127413603 @default.
• W2890366991 hasConceptScore W2890366991C133731056 @default.
• W2890366991 hasConceptScore W2890366991C134146338 @default.
• W2890366991 hasConceptScore W2890366991C191908910 @default.
• W2890366991 hasConceptScore W2890366991C24326235 @default.
• W2890366991 hasConceptScore W2890366991C2780365114 @default.
• W2890366991 hasConceptScore W2890366991C41008148 @default.
• W2890366991 hasConceptScore W2890366991C60644358 @default.
• W2890366991 hasConceptScore W2890366991C86803240 @default.
• W2890366991 hasLocation W28903669911 @default.
• W2890366991 hasOpenAccess W2890366991 @default.
• W2890366991 hasPrimaryLocation W28903669911 @default.
• W2890366991 hasRelatedWork W2033111850 @default.
• W2890366991 hasRelatedWork W2090517830 @default.
• W2890366991 hasRelatedWork W2140046357 @default.
• W2890366991 hasRelatedWork W2216330956 @default.
• W2890366991 hasRelatedWork W2271636366 @default.
• W2890366991 hasRelatedWork W2514509635 @default.
• W2890366991 hasRelatedWork W2528599819 @default.
• W2890366991 hasRelatedWork W2554163170 @default.
• W2890366991 hasRelatedWork W2571166421 @default.
• W2890366991 hasRelatedWork W2584421149 @default.
• W2890366991 hasRelatedWork W2766191773 @default.
• W2890366991 hasRelatedWork W2797414813 @default.
• W2890366991 hasRelatedWork W2883882445 @default.
• W2890366991 hasRelatedWork W2888857063 @default.
• W2890366991 hasRelatedWork W2900657508 @default.
• W2890366991 hasRelatedWork W2913355224 @default.
• W2890366991 hasRelatedWork W3003600829 @default.
• W2890366991 hasRelatedWork W3006113212 @default.
• W2890366991 hasRelatedWork W3091988491 @default.
• W2890366991 hasRelatedWork W9131880 @default.
• W2890366991 isParatext "false" @default.
• W2890366991 isRetracted "false" @default.
• W2890366991 magId "2890366991" @default.
• W2890366991 workType "dissertation" @default.