Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior.

ABSTRACT: Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems can come together to yield complex and life-like behaviors remains a key question. Herein, we illustrate how the combination of automated experimentation and image processing, physicochemical analysis, and machine learning allows significant advances to be made in understanding the driving forces behind oil-in-water droplet behaviors. Utilizing >7,000 experiments collected using an autonomous robotic platform, we illustrate how smart automation cannot only help with exploration, optimization, and discovery of new behaviors, but can also be core

SUBMITTER: Points LJ 

PROVIDER: S-EPMC5798325 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature