Impact framework

Impact framework provides programmatic, reproducible data analysis workflows in Python for interpreting, modeling, and visualizing large heterogeneous datasets from microbial physiology and genetic engineering design–build–test cycles.

Key Features:

• Reproducible programmatic workflows: Enables creation of reproducible and extensible Python workflows tailored to microbial engineering and physiology analyses.
• Analysis tool suite: Provides a suite of tools that support stages of data analysis from initial interpretation through detailed physiological characterization.
• Visualization capabilities: Translates complex, heterogeneous biological datasets into visual formats for interpretation and communication.
• Throughput facilitation: Mediates data-analysis bottlenecks to enhance the throughput of microbial engineering projects and iterative phenotype optimization.

Scientific Applications:

• Design–build–test cycles: Supports data analysis and interpretation across iterative genetic engineering workflows for microorganisms.
• Microbial physiology characterization: Facilitates interpretation and modeling of physiological data for engineered microbes.
• High-throughput experiment integration: Handles large, heterogeneous datasets generated by DNA synthesis and assembly, liquid handling automation, and scale-down characterization platforms.
• Phenotype optimization: Enables modeling and visualization to track and guide stepwise progress toward desired microbial phenotypes.

Methodology:

Implements Python-based, programmatic, reproducible workflows for interpretation, modeling, and visualization of heterogeneous microbial physiology and engineering datasets.