ArticleACS synthetic biology2022
LOICA: Integrating Models with Data for Genetic Network Design Automation.
Article in ACS synthetic biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A tool for modeling gene regulatory networks (GRN_modeler) and its applications to synthetic biology.Molecular systems biology · 2025Article
- Accurate characterization of dynamic microbial gene expression and growth rate profiles.Synthetic biology (Oxford, England) · 2022Article
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Authors and funding
3 authors.
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Abstract
Genetic design automation tools are necessary to expand the scale and complexity of possible synthetic genetic networks. These tools are enabled by abstraction of a hierarchy of standardized components and devices. Abstracted elements must be parametrized from data derived from relevant experiments, and these experiments must be related to the part composition of the abstract components. Here we present Logical Operators for Integrated Cell Algorithms (LOICA), a Python package for designing, modeling, and characterizing genetic networks based on a simple object-oriented design abstraction. LOICA uses classes to represent different biological and experimental components, which generate models through their interactions. These models can be parametrized by direct connection to data contained in Flapjack so that abstracted components of designs can characterize themselves. Models can be simulated using continuous or stochastic methods and the data published and managed using Flapjack. LOICA also outputs SBOL3 descriptions and generates graph representations of genetic network designs.
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Registered trials
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