LOICA

LOICA provides Python-based object-oriented modeling, design, and parameterization of genetic networks to support synthetic biology design-build-test-learn cycles.

Key Features:

• Python implementation: Implemented in Python and supplies computational and mathematical modeling capabilities relevant to genetic design automation.
• Object-oriented abstraction: Represents biological and experimental components as classes to encapsulate elements of genetic circuits.
• Hierarchical composition: Enables composition of abstract elements into hierarchical structures including components, devices, and systems.
• Model generation: Generates models from interactions among classes to represent genetic network behavior.
• SynBioHub integration: Connects high-level designs to their constituent parts via SynBioHub.
• Flapjack interface: Interfaces with Flapjack to link experimental data and support data management and analysis.
• Data-driven parameterization: Enables parameterization of models based on empirical experimental measurements.
• Support for DBTL cycle: Supports the design-build-test-learn cycle by connecting theoretical models to experimental data for iterative refinement.

Scientific Applications:

• Genetic circuit design and simulation: Design, model, and simulate genetic circuits and networks within synthetic biology projects.
• Model-based characterization: Characterize genetic components and systems by fitting and testing models against experimental data.
• Data-driven parameter inference: Derive model parameters from experimental measurements stored and managed through Flapjack.
• Genetic design automation support: Map high-level designs to parts repositories via SynBioHub to enable genetic design automation workflows.

Methodology:

LOICA uses an object-oriented design abstraction in which biological and experimental components are represented as classes composed into hierarchical components, devices, and systems; models are generated from interactions among these classes and parameterized using experimental data linked via SynBioHub and Flapjack.