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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

Authors :
Sanders, Lauren M.
Yang, Jason H.
Scott, Ryan T.
Qutub, Amina Ann
Martin, Hector Garcia
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
Soboczenski, Frank
Snyder, Michael
Soman, Karthik
Theriot, Corey A.
Van Valen, David
Venkateswaran, Kasthuri
Warren, Liz
Worthey, Liz
Zitnik, Marinka
Costes, Sylvain V.
Publication Year :
2021

Abstract

Space biology research aims to understand fundamental effects of spaceflight 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-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space.<br />Comment: 28 pages, 4 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2112.12582
Document Type :
Working Paper