학술논문
Biological research and self-driving labs in deep space supported by artificial intelligence
Document Type
Review Paper
Author
Sanders, Lauren M.; Scott, Ryan T.; Yang, Jason H.; Qutub, Amina Ann; Garcia Martin, Hector; Berrios, Daniel C.; Hastings, Jaden J. A.; Rask, Jon; Mackintosh, Graham; Hoarfrost, Adrienne L.; Chalk, Stuart; Kalantari, John; Khezeli, Kia; Antonsen, Erik L.; Babdor, Joel; Barker, Richard; Baranzini, Sergio E.; Beheshti, Afshin; Delgado-Aparicio, Guillermo M.; Glicksberg, Benjamin S.; Greene, Casey S.; Haendel, Melissa; Hamid, Arif A.; Heller, Philip; Jamieson, Daniel; Jarvis, Katelyn J.; Komarova, Svetlana V.; Komorowski, Matthieu; Kothiyal, Prachi; Mahabal, Ashish; Manor, Uri; Mason, Christopher E.; Matar, Mona; Mias, George I.; Miller, Jack; Myers, Jr., Jerry G.; Nelson, Charlotte; Oribello, Jonathan; Park, Seung-min; Parsons-Wingerter, Patricia; Prabhu, R. K.; Reynolds, Robert J.; Saravia-Butler, Amanda; Saria, Suchi; Sawyer, Aenor; Singh, Nitin Kumar; Snyder, Michael; Soboczenski, Frank; Soman, Karthik; Theriot, Corey A.; Van Valen, David; Venkateswaran, Kasthuri; Warren, Liz; Worthey, Liz; Zitnik, Marinka; Costes, Sylvain V.
Source
Nature Machine Intelligence. 5(3):208-219
Subject
Language
English
ISSN
2522-5839
Abstract
Space biology research aims to understand fundamental spaceflight effects on organisms, develop foundational knowledge to support deep space exploration and, ultimately, bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data and model organisms from both spaceborne and ground-analogue studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally automated, light, agile and intelligent to accelerate knowledge discovery. Here we present a summary of decadal recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning and modelling applications that offer solutions to these space biology challenges. The integration of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modelling and analytics, support maximally automated and reproducible experiments, and efficiently manage spaceborne data and metadata, ultimately to enable life to thrive in deep space.
Deep space exploration missions will require new technologies that can support astronaut health systems, as well as biological monitoring and research systems that can function independently from Earth-based mission control centres. A NASA workshop explored how artificial intelligence advances could help address these challenges and, in this second of two Review articles based on the findings from the workshop, the intersection between artificial intelligence and space biology is discussed.
Deep space exploration missions will require new technologies that can support astronaut health systems, as well as biological monitoring and research systems that can function independently from Earth-based mission control centres. A NASA workshop explored how artificial intelligence advances could help address these challenges and, in this second of two Review articles based on the findings from the workshop, the intersection between artificial intelligence and space biology is discussed.