Biological research and self-driving labs in deep space supported by artificial intelligence

太空探索 计算机科学 空格(标点符号) 美国宇航局深空网络 太空飞行 领域(数学) 数据科学 火星探测计划 人工智能 火星探测 航天器 系统工程 工程类 天体生物学 航空航天工程 生物 数学 纯数学 操作系统
作者
Lauren Sanders,Ryan T. Scott,Jason H. Yang,Amina A. Qutub,Héctor García Martín,Daniel C. Berrios,Jaden J. A. Hastings,Jon Rask,Graham Mackintosh,Adrienne Hoarfrost,Stuart Chalk,John Kalantari,Kia Khezeli,Erik L. Antonsen,Joël Babdor,Richard Barker,Sergio E. Baranzini,Afshin Beheshti,Guillermo M. Delgado-Aparicio,Benjamin S. Glicksberg,Casey S. Greene,Melissa Haendel,Arif Hamid,Philip Heller,Daniel Jamieson,Katelyn Jarvis,Svetlana V. Komarova,Matthieu Komorowski,Prachi Kothiyal,A. Mahabal,Uri Manor,Christopher E. Mason,Mona Matar,George I. Mias,J. Miller,Jerry G. Myers,Charlotte Nelson,Jonathan Oribello,Seung Min Park,Patricia Parsons‐Wingerter,Raj Prabhu,Robert J. Reynolds,Amanda Saravia-Butler,Suchi Saria,Aenor Sawyer,Nitin K. Singh,M Snyder,Frank Soboczenski,Karthik Soman,Corey A. Theriot,David Van Valen,Kasthuri Venkateswaran,L. E. Warren,Liz Worthey,Marinka Žitnik,Sylvain V. Costes
出处
期刊:Nature Machine Intelligence [Springer Nature]
卷期号:5 (3): 208-219 被引量:16
标识
DOI:10.1038/s42256-023-00618-4
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
challenger发布了新的文献求助10
1秒前
helly完成签到,获得积分10
1秒前
2秒前
儒雅儒雅完成签到,获得积分10
2秒前
bkagyin应助废柴采纳,获得10
3秒前
3秒前
3秒前
Akim应助友好诗柳采纳,获得10
3秒前
4秒前
凉白开144完成签到,获得积分10
4秒前
斯文败类应助谦让若蕊采纳,获得10
4秒前
4秒前
Dr.Liujun完成签到,获得积分10
4秒前
5秒前
超喜欢你发布了新的文献求助10
6秒前
6秒前
零度空间发布了新的文献求助10
7秒前
艺yi完成签到,获得积分10
7秒前
7秒前
一行白鹭上青天完成签到,获得积分10
8秒前
zhangzhen完成签到,获得积分10
8秒前
ysy关注了科研通微信公众号
8秒前
8秒前
dreamland发布了新的文献求助10
9秒前
alexhua完成签到,获得积分20
9秒前
Bolin发布了新的文献求助10
10秒前
Xv发布了新的文献求助10
10秒前
眰恦完成签到 ,获得积分10
10秒前
陈某人发布了新的文献求助10
10秒前
慕青应助鲤鱼怀绿采纳,获得10
10秒前
yanyan发布了新的文献求助10
10秒前
11秒前
一一一完成签到 ,获得积分10
11秒前
大个应助lee采纳,获得10
12秒前
好困应助土豆丝采纳,获得10
13秒前
Owen应助Kenny采纳,获得10
13秒前
13秒前
犹豫小懒虫应助wuliumu采纳,获得10
13秒前
13秒前
14秒前
高分求助中
Medicina di laboratorio. Logica e patologia clinica 600
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
Sarcolestes leedsi Lydekker, an ankylosaurian dinosaur from the Middle Jurassic of England 500
Machine Learning for Polymer Informatics 500
《关于整治突出dupin问题的实施意见》(厅字〔2019〕52号) 500
2024 Medicinal Chemistry Reviews 480
Geochemistry, 2nd Edition 地球化学经典教科书第二版 401
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3217051
求助须知:如何正确求助?哪些是违规求助? 2866215
关于积分的说明 8150967
捐赠科研通 2532896
什么是DOI,文献DOI怎么找? 1365956
科研通“疑难数据库(出版商)”最低求助积分说明 644636
邀请新用户注册赠送积分活动 617579