A Proposed Paradigm for Collecting Big Data in Life Science - Erika Alden DeBenedictis

Wednesday 12th of October 2022 - 5pm BST, 6pm CEST, 12noon EDT, 9am PDT - On Zoom

Abstract: Recent machine learning successes like Alphafold II highlight the utility of large, high-fidelity datasets in life science. The Bioautomation Challenge is launching a new program called The Open Dataset Initiative that experiments with a new paradigm for funding, collecting, and sharing such datasets. This program will create a portfolio of robust experimental cloud lab techniques and allow scientists worldwide to submit samples for analysis. The resulting standardized measurements populate a public database after an embargo period. n

Speaker biography: Erika is a former astronomer and current synthetic biologist. As an undergraduate at Caltech, Erika worked on topics in computational physics including space mission orbit design at NASA and computational protein design at D. E. Shaw Research. Erika worked with Kevin Esvelt at MIT during her PhD, where she used laboratory automation to tackle problems in synthetic biology. In collaboration with Schmidt Futures, she recently launched the 2022 Bioautomation Challenge, a grant program that improves the reproducibility, scalability, and shareability of life science research with programmable experiments. She now leads the Biodesign Laboratory at the Francis Crick Institute in London, UK. Her lab uses Robotics-Accelerated Evolution to push the limits of biotech for use on Earth and in Space.

PyLabRobot: A Universal Interface for Liquid-Handling Robots - Stefan Golas

Wednesday 19th of October 2022 - 5pm BST, 6pm CEST, 12noon EDT, 9am PDT - On Zoom

Abstract: PyLabRobot is a Python library that provides a hardware-agnostic programming interface to liquid-handling robots based on a universal model of their functionality. PyLabRobot provides an extensible framework for instantiating device drivers to different models of robots that can enact commands issued from a high-level, device agnostic interface. This is based on a set of abstract base classes that define general liquid-handling commands, which are then implemented in robot device drivers. Development of new robot scripts and applications is fundamentally streamlined by allowing developers to access open-source code ecosystems. The abstraction of high-level commands from specific hardware implementations means that general-purpose applications can be created and reused across different robots and controllers.