research-article

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Composable Modular Models for Synthetic Biology

Authors:

Goksel Misirli,

Jennifer Hallinan,

Anil WipatAuthors Info & Claims

ACM Journal on Emerging Technologies in Computing Systems (JETC), Volume 11, Issue 3

Article No.: 22, Pages 1 - 19

https://doi.org/10.1145/2631921

Published: 30 December 2014 Publication History

Abstract

Modelling and computational simulation are crucial for the large-scale engineering of biological circuits since they allow the system under design to be simulated prior to implementation in vivo. To support automated, model-driven design it is desirable that in silico models are modular, composable and use standard formats. The synthetic biology design process typically involves the composition of genetic circuits from individual parts. At the most basic level, these parts are representations of genetic features such as promoters, ribosome binding sites (RBSs), and coding sequences (CDSs). However, it is also desirable to model the biological molecules and behaviour that arise when these parts are combined in vivo. Modular models of parts can be composed and their associated systems simulated, facilitating the process of model-centred design. The availability of databases of modular models is essential to support software tools used in the model-driven design process. In this article, we present an approach to support the development of composable, modular models for synthetic biology, termed Standard Virtual Parts. We then describe a programmatically accessible and publicly available database of these models to allow their use by computational design tools.

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Cited By

Buecherl LMyers CFontanarrosa P(2024)Evaluating the Contribution of Model Complexity in Predicting Robustness in Synthetic Genetic CircuitsACS Synthetic Biology10.1021/acssynbio.3c00708Online publication date: 12-Sep-2024
https://doi.org/10.1021/acssynbio.3c00708
Wang BYang HSun JDou CHuang JGuo F(2021)BioMaster: An Integrated Database and Analytic Platform to Provide Comprehensive Information About BioBrick PartsFrontiers in Microbiology10.3389/fmicb.2021.59397912Online publication date: 21-Jan-2021
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Buecherl LRoberts RFontanarrosa PThomas PMante JZhang ZMyers C(2021)Stochastic Hazard Analysis of Genetic Circuits in iBioSim and STAMINAACS Synthetic Biology10.1021/acssynbio.1c0015910:10(2532-2540)Online publication date: 4-Oct-2021
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Index Terms

Composable Modular Models for Synthetic Biology
1. Applied computing

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Published In

cover image ACM Journal on Emerging Technologies in Computing Systems

ACM Journal on Emerging Technologies in Computing Systems Volume 11, Issue 3

Special Issue on Computational Synthetic Biology and Regular Papers

December 2014

219 pages

ISSN:1550-4832

EISSN:1550-4840

DOI:10.1145/2711453

Editor:
Krishnendu Chakrabarty
Duke University, USA

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Copyright © 2014 Owner/Author.

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 30 December 2014

Accepted: 01 May 2014

Revised: 01 April 2014

Received: 01 January 2014

Published in JETC Volume 11, Issue 3

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Buecherl LMyers CFontanarrosa P(2024)Evaluating the Contribution of Model Complexity in Predicting Robustness in Synthetic Genetic CircuitsACS Synthetic Biology10.1021/acssynbio.3c00708Online publication date: 12-Sep-2024
https://doi.org/10.1021/acssynbio.3c00708
Wang BYang HSun JDou CHuang JGuo F(2021)BioMaster: An Integrated Database and Analytic Platform to Provide Comprehensive Information About BioBrick PartsFrontiers in Microbiology10.3389/fmicb.2021.59397912Online publication date: 21-Jan-2021
https://doi.org/10.3389/fmicb.2021.593979
Buecherl LRoberts RFontanarrosa PThomas PMante JZhang ZMyers C(2021)Stochastic Hazard Analysis of Genetic Circuits in iBioSim and STAMINAACS Synthetic Biology10.1021/acssynbio.1c0015910:10(2532-2540)Online publication date: 4-Oct-2021
https://doi.org/10.1021/acssynbio.1c00159
Mısırlı GYang BJames KWipat A(2021)Virtual Parts Repository 2: Model-Driven Design of Genetic Regulatory CircuitsACS Synthetic Biology10.1021/acssynbio.1c0015710:12(3304-3315)Online publication date: 11-Nov-2021
https://doi.org/10.1021/acssynbio.1c00157
McLaughlin JBeal JMısırlı GGrünberg RBartley BScott-Brown JVaidyanathan PFontanarrosa POberortner EWipat AGorochowski TMyers C(2020)The Synthetic Biology Open Language (SBOL) Version 3: Simplified Data Exchange for BioengineeringFrontiers in Bioengineering and Biotechnology10.3389/fbioe.2020.010098Online publication date: 11-Sep-2020
https://doi.org/10.3389/fbioe.2020.01009
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Mısırlı GTaylor RGoñi-Moreno AMcLaughlin JMyers CGennari JLord PWipat A(2019)SBOL-OWL: An Ontological Approach for Formal and Semantic Representation of Synthetic Biology InformationACS Synthetic Biology10.1021/acssynbio.8b005328:7(1498-1514)Online publication date: 6-May-2019
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Neal MKönig MNickerson DMısırlı GKalbasi RDräger AAtalag KChelliah VCooling MCook DCrook Sde Alba MFriedman SGarny AGennari JGleeson PGolebiewski MHucka MJuty NMyers COlivier BSauro HScharm MSnoep JTouré VWipat AWolkenhauer OWaltemath D(2018)Harmonizing semantic annotations for computational models in biologyBriefings in Bioinformatics10.1093/bib/bby087Online publication date: 21-Nov-2018
https://doi.org/10.1093/bib/bby087
Waites WMısırlı GCavaliere MDanos VWipat A(2018)A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and InferenceACS Synthetic Biology10.1021/acssynbio.8b002017:12(2812-2823)Online publication date: 8-Nov-2018
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Misirli GNguyen TMcLaughlin JVaidyanathan PJones TDensmore DMyers CWipat A(2018)A Computational Workflow for the Automated Generation of Models of Genetic DesignsACS Synthetic Biology10.1021/acssynbio.7b004598:7(1548-1559)Online publication date: 21-May-2018
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