INCAWrapper: a Python wrapper for INCA for seamless data import, -export, and -processing.

Motivation: INCA is a powerful tool for metabolic flux analysis, however, import and export of data and results can be tedious and limit the use of INCA in automated workflows.

Results: The INCAWrapper enables the use of INCA purely through Python, which allows the use of INCA in common data science workflows.

Availability And Implementation: The INCAWrapper is implemented in Python and can be found at https://github.

Low-quality animal by-product streams for the production of PHA-biopolymers: fats, fat/protein-emulsions and materials with high ash content as low-cost feedstocks.

Objective: The rapid accumulation of crude-oil based plastics in the environment is posing a fundamental threat to the future of mankind. The biodegradable and bio-based polyhydroxyalkanoates (PHAs) can replace conventional plastics, however, their current production costs are not competitive and therefore prohibiting PHAs from fulfilling their potential.

Results: Different low-quality animal by-products, which were separated by thermal hydrolysis into a fat-, fat/protein-emulsion- and mineral-fat-mixture- (material with high ash content) phase, were successfully screened as carbon sources for the production of PHA.