Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology

Boeing, Philipp; Leon, Miriam; Nesbeth, Darren N.; Finkelstein, Anthony; Barnes, C.

doi:10.3390/pr6090167

Cited by 7 publications

(6 citation statements)

References 82 publications

(102 reference statements)

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“…It involves systematically exploring all possible states and transitions of a model to check if certain properties or specifications hold true. Model-checking techniques typically involve the following steps [12] :…”

Section: Research Background and Literature Reviewmentioning

confidence: 99%

“…AOP is a programming paradigm that separates out and abstracts away problems that affect many parts of a system [11]. AOP has been successfully employed in numerous domains [12] [13] to improve the modularity, maintainability, and evolvability of software systems. This research presents a novel method that harnesses AOP to analyze and perform model checking on the dynamic behaviors exhibited by blockchain systems.…”

Section: Introductionmentioning

confidence: 99%

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BlockASP: A Framework for AOP-Based Model Checking Blockchain System

AlSobeh,

Magableh

2023

IEEE Access

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Blockchain systems are lauded for their security and reliability. Security is a cornerstone, as they employ cryptographic techniques to ensure the immutability of data, making it extremely resistant to tampering. With decentralized networks, they also reduce the risk of a single point of failure, enhancing reliability. Model checking plays a vital role in ensuring the security and reliability of blockchain systems. However, traditional model-checking approaches face challenges in handling the inherent dynamism exhibited in blockchain systems. To overcome this challenge, Aspect-Oriented programming (AOP) offers capabilities to enhance blockchain model checking through the modularization of cross-cutting concerns, enabling traceability and monitoring, facilitating dynamic instrumentation, and supporting fine-grained property specifications. The aim of this research is to enable more effective and efficient verification of dynamic behaviors in blockchain systems compared to conventional model-checking techniques using AOP. As a result, this research introduces BlockASP, a novel blockchain model verification method that leverages AOP to analyze and monitor dynamic behavior of the blockchain system. BlockASP integrates the benefits of aspect-orientation and model checking into the blockchain architecture to strengthen security and reliability. This research has examined prior arts that are related to blockchain modeling using Objectoriented (OO) and those that are using AOP. Our research has proposed and discussed the BlockASP technique, the research provided a case study to demonstrate the validity and superiority in facilitating the monitoring of dynamic blockchain behavior using AOP compared to traditional approaches such as Model-Driven Architecture (MDA).

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Section: Research Background and Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BlockASP: A Framework for AOP-Based Model Checking Blockchain System

AlSobeh,

Magableh

2023

IEEE Access

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“…Furthermore, metabolic burden can induce stress responses in the host, increasing mutation rates (Matic, 2013;Couto et al, 2018). Whole cell models, combining the impact of load and metabolic burden, show how changing resource availability in a host strain can produce different circuit behavior (Gorochowski et al, 2016;Boeing et al, 2018). Efforts to reduce load and metabolic burden include optimizing circuits for low copy plasmids or chromosomal integration (Lee et al, 2016), and using orthogonal ribosomes to allocate recombinant gene expression to different resource pools (Darlington et al, 2018;Boo et al, 2019).…”

Section: Limitations Of Monoculture Engineeringmentioning

confidence: 99%

From Microbial Communities to Distributed Computing Systems

Karkaria¹,

Treloar²,

Barnes³

et al. 2020

Front. Bioeng. Biotechnol.

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A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

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“…Computer-aided design is a key component for the efficient engineering of biological systems [1][2][3]. The development of functional synthetic biological circuits is usually hampered by the high levels of uncertainty encountered at different scales.…”

Section: Introductionmentioning

confidence: 99%

Distilling Robust Design Principles of Biocircuits Using Mixed Integer Dynamic Optimization

Otero-Muras

Banga

2019

Processes

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A major challenge in model-based design of synthetic biochemical circuits is how to address uncertainty in the parameters. A circuit whose behavior is robust to variations in the parameters will have more chances to behave as predicted when implemented in practice, and also to function reliably in presence of fluctuations and noise. Here, we extend our recent work on automated-design based on mixed-integer multi-criteria dynamic optimization to take into account parametric uncertainty. We exploit the intensive sampling of the design space performed by a global optimization algorithm to obtain the robustness of the topologies without significant additional computational effort. Our procedure provides automatically topologies that best trade-off performance and robustness against parameter fluctuations. We illustrate our approach considering the automated design of gene circuits achieving adaptation.

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Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology

Cited by 7 publications

References 82 publications

BlockASP: A Framework for AOP-Based Model Checking Blockchain System

BlockASP: A Framework for AOP-Based Model Checking Blockchain System

From Microbial Communities to Distributed Computing Systems

Distilling Robust Design Principles of Biocircuits Using Mixed Integer Dynamic Optimization

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