{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T08:50:18Z","timestamp":1772787018182,"version":"3.50.1"},"reference-count":167,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T00:00:00Z","timestamp":1679529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T00:00:00Z","timestamp":1679529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Mach Intell"],"DOI":"10.1038\/s42256-023-00618-4","type":"journal-article","created":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T17:03:19Z","timestamp":1679590999000},"page":"208-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Biological research and self-driving labs in deep space supported by artificial intelligence"],"prefix":"10.1038","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9393-0861","authenticated-orcid":false,"given":"Lauren M.","family":"Sanders","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0654-5661","authenticated-orcid":false,"given":"Ryan T.","family":"Scott","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0921-4657","authenticated-orcid":false,"given":"Jason H.","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Amina Ann","family":"Qutub","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4556-9685","authenticated-orcid":false,"given":"Hector","family":"Garcia Martin","sequence":"additional","affiliation":[]},{"given":"Daniel C.","family":"Berrios","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1459-3364","authenticated-orcid":false,"given":"Jaden J. A.","family":"Hastings","sequence":"additional","affiliation":[]},{"given":"Jon","family":"Rask","sequence":"additional","affiliation":[]},{"given":"Graham","family":"Mackintosh","sequence":"additional","affiliation":[]},{"given":"Adrienne L.","family":"Hoarfrost","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0703-7776","authenticated-orcid":false,"given":"Stuart","family":"Chalk","sequence":"additional","affiliation":[]},{"given":"John","family":"Kalantari","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1982-9391","authenticated-orcid":false,"given":"Kia","family":"Khezeli","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1042-7011","authenticated-orcid":false,"given":"Erik L.","family":"Antonsen","sequence":"additional","affiliation":[]},{"given":"Joel","family":"Babdor","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5681-9857","authenticated-orcid":false,"given":"Richard","family":"Barker","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0067-194X","authenticated-orcid":false,"given":"Sergio E.","family":"Baranzini","sequence":"additional","affiliation":[]},{"given":"Afshin","family":"Beheshti","sequence":"additional","affiliation":[]},{"given":"Guillermo M.","family":"Delgado-Aparicio","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4515-8090","authenticated-orcid":false,"given":"Benjamin S.","family":"Glicksberg","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8713-9213","authenticated-orcid":false,"given":"Casey S.","family":"Greene","sequence":"additional","affiliation":[]},{"given":"Melissa","family":"Haendel","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7403-0067","authenticated-orcid":false,"given":"Arif A.","family":"Hamid","sequence":"additional","affiliation":[]},{"given":"Philip","family":"Heller","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"Jamieson","sequence":"additional","affiliation":[]},{"given":"Katelyn J.","family":"Jarvis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3570-3147","authenticated-orcid":false,"given":"Svetlana V.","family":"Komarova","sequence":"additional","affiliation":[]},{"given":"Matthieu","family":"Komorowski","sequence":"additional","affiliation":[]},{"given":"Prachi","family":"Kothiyal","sequence":"additional","affiliation":[]},{"given":"Ashish","family":"Mahabal","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9802-1955","authenticated-orcid":false,"given":"Uri","family":"Manor","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1850-1642","authenticated-orcid":false,"given":"Christopher E.","family":"Mason","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4122-7207","authenticated-orcid":false,"given":"Mona","family":"Matar","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9083-1216","authenticated-orcid":false,"given":"George I.","family":"Mias","sequence":"additional","affiliation":[]},{"given":"Jack","family":"Miller","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9775-4850","authenticated-orcid":false,"suffix":"Jr.","given":"Jerry G.","family":"Myers","sequence":"additional","affiliation":[]},{"given":"Charlotte","family":"Nelson","sequence":"additional","affiliation":[]},{"given":"Jonathan","family":"Oribello","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2123-6245","authenticated-orcid":false,"given":"Seung-min","family":"Park","sequence":"additional","affiliation":[]},{"given":"Patricia","family":"Parsons-Wingerter","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6073-4802","authenticated-orcid":false,"given":"R. K.","family":"Prabhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1070-8996","authenticated-orcid":false,"given":"Robert J.","family":"Reynolds","sequence":"additional","affiliation":[]},{"given":"Amanda","family":"Saravia-Butler","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7667-5210","authenticated-orcid":false,"given":"Suchi","family":"Saria","sequence":"additional","affiliation":[]},{"given":"Aenor","family":"Sawyer","sequence":"additional","affiliation":[]},{"given":"Nitin Kumar","family":"Singh","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0784-7987","authenticated-orcid":false,"given":"Michael","family":"Snyder","sequence":"additional","affiliation":[]},{"given":"Frank","family":"Soboczenski","sequence":"additional","affiliation":[]},{"given":"Karthik","family":"Soman","sequence":"additional","affiliation":[]},{"given":"Corey A.","family":"Theriot","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7534-7621","authenticated-orcid":false,"given":"David","family":"Van Valen","sequence":"additional","affiliation":[]},{"given":"Kasthuri","family":"Venkateswaran","sequence":"additional","affiliation":[]},{"given":"Liz","family":"Warren","sequence":"additional","affiliation":[]},{"given":"Liz","family":"Worthey","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8530-7228","authenticated-orcid":false,"given":"Marinka","family":"Zitnik","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8542-2389","authenticated-orcid":false,"given":"Sylvain V.","family":"Costes","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,23]]},"reference":[{"key":"618_CR1","doi-asserted-by":"publisher","first-page":"1162","DOI":"10.1016\/j.cell.2020.10.050","volume":"183","author":"E Afshinnekoo","year":"2020","unstructured":"Afshinnekoo, E. et al. Fundamental biological features of spaceflight: advancing the field to enable deep-space exploration. Cell 183, 1162\u20131184 (2020).","journal-title":"Cell"},{"key":"618_CR2","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/s11038-010-9376-x","volume":"107","author":"DJ Loftus","year":"2010","unstructured":"Loftus, D. J., Rask, J. C., McCrossin, C. G. & Tranfield, E. M. The chemical reactivity of lunar dust: from toxicity to astrobiology. Earth Moon Planets 107, 95\u2013105 (2010).","journal-title":"Earth Moon Planets"},{"key":"618_CR3","doi-asserted-by":"crossref","unstructured":"Pohlen, M., Carroll, D., Prisk, G. K. & Sawyer, A. J. Overview of lunar dust toxicity risk. NPJ Microgravity 8, 55 (2022).","DOI":"10.1038\/s41526-022-00244-1"},{"key":"618_CR4","unstructured":"Paul, A.-L. & Ferl, R. J. The biology of low atmospheric pressure\u2013implications for exploration mission design and advanced life support. Am. Soc. Gravit. Space Biol. 19, 3\u201317 (2005)."},{"key":"618_CR5","unstructured":"Council, N. R. Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era (National Academies Press, 2011)."},{"key":"618_CR6","doi-asserted-by":"publisher","first-page":"1645","DOI":"10.1007\/s00421-012-2507-5","volume":"113","author":"N Goswami","year":"2013","unstructured":"Goswami, N. et al. Maximizing information from space data resources: a case for expanding integration across research disciplines. Eur. J. Appl. Physiol. 113, 1645\u20131654 (2013).","journal-title":"Eur. J. Appl. Physiol."},{"key":"618_CR7","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1038\/s41587-020-0485-4","volume":"38","author":"SN Nangle","year":"2020","unstructured":"Nangle, S. N. et al. The case for biotech on Mars. Nat. Biotechnol. 38, 401\u2013407 (2020).","journal-title":"Nat. Biotechnol."},{"key":"618_CR8","doi-asserted-by":"publisher","unstructured":"Costes, S. V., Sanders, L. M. & Scott, R. T. Workshop on Artificial Intelligence & Modeling for Space Biology. Zenodo https:\/\/doi.org\/10.5281\/zenodo.7508535 (2023).","DOI":"10.5281\/zenodo.7508535"},{"key":"618_CR9","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1126\/science.aaa8415","volume":"349","author":"MI Jordan","year":"2015","unstructured":"Jordan, M. I. & Mitchell, T. M. Machine learning: trends, perspectives, and prospects. Science 349, 255\u2013260 (2015).","journal-title":"Science"},{"key":"618_CR10","unstructured":"Topol, E. J. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again (Basic Books, 2019)."},{"key":"618_CR11","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","volume":"25","author":"EJ Topol","year":"2019","unstructured":"Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 44\u201356 (2019).","journal-title":"Nat. Med."},{"key":"618_CR12","doi-asserted-by":"publisher","unstructured":"Scott, R. T. et al. Biomonitoring and precision health in deep space supported by artificial intelligence. Nat. Mach. Intell. https:\/\/doi.org\/10.1038\/s42256-023-00617-5 (2023).","DOI":"10.1038\/s42256-023-00617-5"},{"key":"618_CR13","unstructured":"National Academies of Sciences, Engineering, and Medicine, Policy and Global Affairs, Board on Research Data and Information & Committee on Toward an Open Science Enterprise Open Science by Design: Realizing a Vision for 21st Century Research (National Academies Press, 2018)."},{"key":"618_CR14","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.18","volume":"3","author":"MD Wilkinson","year":"2016","unstructured":"Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).","journal-title":"Sci. Data"},{"key":"618_CR15","first-page":"232","volume":"2018","author":"DC Berrios","year":"2018","unstructured":"Berrios, D. C., Beheshti, A. & Costes, S. V. FAIRness and usability for open-access omics data systems. AMIA Annu. Symp. Proc. 2018, 232\u2013241 (2018).","journal-title":"AMIA Annu. Symp. Proc."},{"key":"618_CR16","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1007\/s11095-019-2742-0","volume":"37","author":"LA Low","year":"2019","unstructured":"Low, L. A. & Giulianotti, M. A. Tissue chips in space: modeling human diseases in microgravity. Pharm. Res. 37, 8 (2019).","journal-title":"Pharm. Res."},{"key":"618_CR17","unstructured":"Ronca, A. E., Souza, K. A. & Mains, R. C. (eds) Translational Cell and Animal Research in Space: 1965\u20132011 NASA Special Publication NASA\/SP-2015-625 (NASA Ames Research Center, 2016)."},{"key":"618_CR18","doi-asserted-by":"crossref","unstructured":"Alwood, J. S. et al. From the bench to exploration medicine: NASA life sciences translational research for human exploration and habitation missions. NPJ Microgravity 3, 5 (2017).","DOI":"10.1038\/s41526-016-0002-8"},{"key":"618_CR19","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1016\/S0094-5765(01)00116-3","volume":"49","author":"H Schatten","year":"2001","unstructured":"Schatten, H., Lewis, M. L. & Chakrabarti, A. Spaceflight and clinorotation cause cytoskeleton and mitochondria changes and increases in apoptosis in cultured cells. Acta Astronaut. 49, 399\u2013418 (2001).","journal-title":"Acta Astronaut."},{"key":"618_CR20","doi-asserted-by":"publisher","first-page":"1489","DOI":"10.1038\/s41423-019-0346-6","volume":"18","author":"L Shi","year":"2021","unstructured":"Shi, L. et al. Spaceflight and simulated microgravity suppresses macrophage development via altered RAS\/ERK\/NF\u03baB and metabolic pathways. Cell. Mol. Immunol. 18, 1489\u20131502 (2021).","journal-title":"Cell. Mol. Immunol."},{"key":"618_CR21","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1089\/ast.2014.1210","volume":"15","author":"RJ Ferl","year":"2015","unstructured":"Ferl, R. J., Koh, J., Denison, F. & Paul, A.-L. Spaceflight induces specific alterations in the proteomes of Arabidopsis. Astrobiology 15, 32\u201356 (2015).","journal-title":"Astrobiology"},{"key":"618_CR22","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.mrfmmm.2008.12.004","volume":"662","author":"X Ou","year":"2009","unstructured":"Ou, X. et al. Spaceflight induces both transient and heritable alterations in DNA methylation and gene expression in rice (Oryza sativa L.). Mutat. Res. 662, 44\u201353 (2009).","journal-title":"Mutat. Res."},{"key":"618_CR23","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-49453-x","volume":"9","author":"EG Overbey","year":"2019","unstructured":"Overbey, E. G. et al. Spaceflight influences gene expression, photoreceptor integrity, and oxidative stress-related damage in the murine retina. Sci. Rep. 9, 13304 (2019).","journal-title":"Sci. Rep."},{"key":"618_CR24","doi-asserted-by":"crossref","unstructured":"Cl\u00e9ment, G. & Slenzka, K. Fundamentals of Space Biology: Research on Cells, Animals, and Plants in Space (Springer Science & Business Media, 2006).","DOI":"10.1007\/0-387-37940-1"},{"key":"618_CR25","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1111\/cts.12689","volume":"13","author":"CK Yeung","year":"2020","unstructured":"Yeung, C. K. et al. Tissue chips in space-challenges and opportunities. Clin. Transl. Sci. 13, 8\u201310 (2020).","journal-title":"Clin. Transl. Sci."},{"key":"618_CR26","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1038\/s41573-020-0079-3","volume":"20","author":"LA Low","year":"2021","unstructured":"Low, L. A., Mummery, C., Berridge, B. R., Austin, C. P. & Tagle, D. A. Organs-on-chips: into the next decade. Nat. Rev. Drug Discov. 20, 345\u2013361 (2021).","journal-title":"Nat. Rev. Drug Discov."},{"key":"618_CR27","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1152\/japplphysiol.00997.2015","volume":"120","author":"RK Globus","year":"2016","unstructured":"Globus, R. K. & Morey-Holton, E. Hindlimb unloading: rodent analog for microgravity. J. Appl. Physiol. 120, 1196\u20131206 (2016).","journal-title":"J. Appl. Physiol."},{"key":"618_CR28","doi-asserted-by":"publisher","first-page":"e3000669","DOI":"10.1371\/journal.pbio.3000669","volume":"18","author":"LC Simonsen","year":"2020","unstructured":"Simonsen, L. C., Slaba, T. C., Guida, P. & Rusek, A. NASA\u2019s first ground-based Galactic cosmic ray simulator: enabling a new era in space radiobiology research. PLoS Biol. 18, e3000669 (2020).","journal-title":"PLoS Biol."},{"key":"618_CR29","unstructured":"Buckey, J. C. Jr & Homick, J. L. The Neurolab Spacelab Mission: Neuroscience Research in Space: Results from the STS-90, Neurolab Spacelab Mission. NASA Technical Reports Server (NASA, 2003)."},{"key":"618_CR30","unstructured":"Diallo, O. N. et al. Impact of the International Space Station Research Results. NASA Technical Reports Server (NASA, 2019)."},{"key":"618_CR31","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.plantsci.2015.11.004","volume":"243","author":"JP Vandenbrink","year":"2016","unstructured":"Vandenbrink, J. P. & Kiss, J. Z. Space, the final frontier: a critical review of recent experiments performed in microgravity. Plant Sci. 243, 115\u2013119 (2016).","journal-title":"Plant Sci."},{"key":"618_CR32","doi-asserted-by":"publisher","unstructured":"Massaro Tieze, S., Liddell, L. C., Santa Maria, S. R. & Bhattacharya, S. BioSentinel: a biological CubeSat for deep space exploration. Astrobiology https:\/\/doi.org\/10.1089\/ast.2019.2068 (2020).","DOI":"10.1089\/ast.2019.2068"},{"key":"618_CR33","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/MAES.2019.2953760","volume":"35","author":"AJ Ricco","year":"2020","unstructured":"Ricco, A. J., Maria, S. R. S., Hanel, R. P. & Bhattacharya, S. BioSentinel: a 6U nanosatellite for deep-space biological science. IEEE Aerospace Electron. Syst. Mag. 35, 6\u201318 (2020).","journal-title":"IEEE Aerospace Electron. Syst. Mag."},{"key":"618_CR34","doi-asserted-by":"publisher","first-page":"3752","DOI":"10.1021\/acs.jproteome.9b00455","volume":"18","author":"Y Chen","year":"2019","unstructured":"Chen, Y. et al. Automated \u2018cells-to-peptides\u2019 sample preparation workflow for high-throughput, quantitative proteomic assays of microbes. J. Proteome Res. 18, 3752\u20133761 (2019).","journal-title":"J. Proteome Res."},{"key":"618_CR35","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.cbpa.2016.12.006","volume":"36","author":"M Zampieri","year":"2017","unstructured":"Zampieri, M., Sekar, K., Zamboni, N. & Sauer, U. Frontiers of high-throughput metabolomics. Curr. Opin. Chem. Biol. 36, 15\u201323 (2017).","journal-title":"Curr. Opin. Chem. Biol."},{"key":"618_CR36","doi-asserted-by":"publisher","first-page":"e1002195","DOI":"10.1371\/journal.pbio.1002195","volume":"13","author":"ZD Stephens","year":"2015","unstructured":"Stephens, Z. D. et al. Big data: astronomical or genomical? PLoS Biol. 13, e1002195 (2015).","journal-title":"PLoS Biol."},{"key":"618_CR37","first-page":"A68","volume":"19","author":"K Tomczak","year":"2015","unstructured":"Tomczak, K., Czerwi\u0144ska, P. & Wiznerowicz, M. The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemp. Oncol. 19, A68\u2013A77 (2015).","journal-title":"Contemp. Oncol."},{"key":"618_CR38","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1038\/ng.2653","volume":"45","author":"J Lonsdale","year":"2013","unstructured":"Lonsdale, J. et al. The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580\u2013585 (2013).","journal-title":"Nat. Genet."},{"key":"618_CR39","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-25557-9","volume":"12","author":"L Atta","year":"2021","unstructured":"Atta, L. & Fan, J. Computational challenges and opportunities in spatially resolved transcriptomic data analysis. Nat. Commun. 12, 5283 (2021).","journal-title":"Nat. Commun."},{"key":"618_CR40","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/s41592-020-01033-y","volume":"18","author":"V Marx","year":"2021","unstructured":"Marx, V. Method of the year: spatially resolved transcriptomics. Nat. Methods 18, 9\u201314 (2021).","journal-title":"Nat. Methods"},{"key":"618_CR41","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1038\/nbt.3423","volume":"34","author":"D Deamer","year":"2016","unstructured":"Deamer, D., Akeson, M. & Branton, D. Three decades of nanopore sequencing. Nat. Biotechnol. 34, 518\u2013524 (2016).","journal-title":"Nat. Biotechnol."},{"key":"618_CR42","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1038\/nprot.2016.182","volume":"12","author":"ER Mardis","year":"2017","unstructured":"Mardis, E. R. DNA sequencing technologies: 2006\u20132016. Nat. Protoc. 12, 213\u2013218 (2017).","journal-title":"Nat. Protoc."},{"key":"618_CR43","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1038\/s41576-019-0093-7","volume":"20","author":"T Stuart","year":"2019","unstructured":"Stuart, T. & Satija, R. Integrative single-cell analysis. Nat. Rev. Genet. 20, 257\u2013272 (2019).","journal-title":"Nat. Rev. Genet."},{"key":"618_CR44","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1016\/j.cell.2019.11.025","volume":"179","author":"M Asp","year":"2019","unstructured":"Asp, M. et al. A spatiotemporal organ-wide gene expression and cell atlas of the developing human heart. Cell 179, 1647\u20131660.e19 (2019).","journal-title":"Cell"},{"key":"618_CR45","doi-asserted-by":"publisher","first-page":"17061","DOI":"10.1038\/nplants.2017.61","volume":"3","author":"S Giacomello","year":"2017","unstructured":"Giacomello, S. et al. Spatially resolved transcriptome profiling in model plant species. Nat Plants 3, 17061 (2017).","journal-title":"Nat Plants"},{"key":"618_CR46","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-44696-0","volume":"9","author":"XW Mao","year":"2019","unstructured":"Mao, X. W. et al. Characterization of mouse ocular response to a 35-day spaceflight mission: evidence of blood-retinal barrier disruption and ocular adaptations. Sci. Rep. 9, 8215 (2019).","journal-title":"Sci. Rep."},{"key":"618_CR47","doi-asserted-by":"publisher","first-page":"e0152877","DOI":"10.1371\/journal.pone.0152877","volume":"11","author":"KR Jonscher","year":"2016","unstructured":"Jonscher, K. R. et al. Spaceflight activates lipotoxic pathways in mouse liver. PLoS ONE 11, e0152877 (2016).","journal-title":"PLoS ONE"},{"key":"618_CR48","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-55869-2","volume":"9","author":"A Beheshti","year":"2019","unstructured":"Beheshti, A. et al. Multi-omics analysis of multiple missions to space reveal a theme of lipid dysregulation in mouse liver. Sci. Rep. 9, 19195 (2019).","journal-title":"Sci. Rep."},{"key":"618_CR49","doi-asserted-by":"publisher","first-page":"108448","DOI":"10.1016\/j.celrep.2020.108448","volume":"33","author":"S Malkani","year":"2020","unstructured":"Malkani, S. et al. Circulating miRNA spaceflight signature reveals targets for countermeasure development. Cell Rep. 33, 108448 (2020).","journal-title":"Cell Rep."},{"key":"618_CR50","doi-asserted-by":"publisher","first-page":"1185","DOI":"10.1016\/j.cell.2020.11.002","volume":"183","author":"WA da Silveira","year":"2020","unstructured":"da Silveira, W. A. et al. Comprehensive multi-omics analysis reveals mitochondrial stress as a central biological hub for spaceflight impact. Cell 183, 1185\u20131201.e20 (2020).","journal-title":"Cell"},{"key":"618_CR51","doi-asserted-by":"publisher","DOI":"10.1186\/s40168-019-0724-4","volume":"7","author":"P Jiang","year":"2019","unstructured":"Jiang, P., Green, S. J., Chlipala, G. E., Turek, F. W. & Vitaterna, M. H. Reproducible changes in the gut microbiome suggest a shift in microbial and host metabolism during spaceflight. Microbiome 7, 113 (2019).","journal-title":"Microbiome"},{"key":"618_CR52","doi-asserted-by":"crossref","unstructured":"Beisel, N. S., Noble, J., Barbazuk, W. B., Paul, A.-L. & Ferl, R. J. Spaceflight-induced alternative splicing during seedling development in Arabidopsis thaliana. NPJ Microgravity 5, 9 (2019).","DOI":"10.1038\/s41526-019-0070-7"},{"key":"618_CR53","doi-asserted-by":"publisher","first-page":"101733","DOI":"10.1016\/j.isci.2020.101733","volume":"23","author":"S-HL Polo","year":"2020","unstructured":"Polo, S.-H. L. et al. RNAseq analysis of rodent spaceflight experiments is confounded by sample collection techniques. iScience 23, 101733 (2020).","journal-title":"iScience"},{"key":"618_CR54","doi-asserted-by":"publisher","first-page":"e0167391","DOI":"10.1371\/journal.pone.0167391","volume":"11","author":"S Choi","year":"2016","unstructured":"Choi, S., Ray, H. E., Lai, S.-H., Alwood, J. S. & Globus, R. K. Preservation of multiple mammalian tissues to maximize science return from ground based and spaceflight experiments. PLoS ONE 11, e0167391 (2016).","journal-title":"PLoS ONE"},{"key":"618_CR55","doi-asserted-by":"publisher","first-page":"e01197","DOI":"10.1002\/aps3.1197","volume":"6","author":"A Krishnamurthy","year":"2018","unstructured":"Krishnamurthy, A., Ferl, R. J. & Paul, A.-L. Comparing RNA-seq and microarray gene expression data in two zones of the Arabidopsis root apex relevant to spaceflight. Appl. Plant Sci. 6, e01197 (2018).","journal-title":"Appl. Plant Sci."},{"key":"618_CR56","doi-asserted-by":"publisher","first-page":"ysab006","DOI":"10.1093\/synbio\/ysab006","volume":"6","author":"J Vrana","year":"2021","unstructured":"Vrana, J. et al. Aquarium: open-source laboratory software for design, execution and data management. Synth. Biol. 6, ysab006 (2021).","journal-title":"Synth. Biol."},{"key":"618_CR57","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1177\/2472630318784506","volume":"23","author":"B Miles","year":"2018","unstructured":"Miles, B. & Lee, P. L. Achieving reproducibility and closed-loop automation in biological experimentation with an IoT-enabled lab of the future. SLAS Technol. 23, 432\u2013439 (2018).","journal-title":"SLAS Technol."},{"key":"618_CR58","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-07668-y","volume":"9","author":"A Durand","year":"2018","unstructured":"Durand, A. et al. A machine learning approach for online automated optimization of super-resolution optical microscopy. Nat. Commun. 9, 5247 (2018).","journal-title":"Nat. Commun."},{"key":"618_CR59","doi-asserted-by":"publisher","first-page":"107537","DOI":"10.1016\/j.biotechadv.2020.107537","volume":"41","author":"JF Hess","year":"2020","unstructured":"Hess, J. F. et al. Library preparation for next generation sequencing: a review of automation strategies. Biotechnol. Adv. 41, 107537 (2020).","journal-title":"Biotechnol. Adv."},{"key":"618_CR60","doi-asserted-by":"publisher","first-page":"8557","DOI":"10.1021\/ac071311w","volume":"79","author":"R G\u00f3mez-Sj\u00f6berg","year":"2007","unstructured":"G\u00f3mez-Sj\u00f6berg, R., Leyrat, A. A., Pirone, D. M., Chen, C. S. & Quake, S. R. Versatile, fully automated, microfluidic cell culture system. Anal. Chem. 79, 8557\u20138563 (2007).","journal-title":"Anal. Chem."},{"key":"618_CR61","doi-asserted-by":"publisher","first-page":"18","DOI":"10.3389\/fbioe.2019.00018","volume":"7","author":"MM Jessop-Fabre","year":"2019","unstructured":"Jessop-Fabre, M. M. & Sonnenschein, N. Improving reproducibility in synthetic biology. Front. Bioeng. Biotechnol. 7, 18 (2019).","journal-title":"Front. Bioeng. Biotechnol."},{"key":"618_CR62","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-10079-2","volume":"10","author":"N Hillson","year":"2019","unstructured":"Hillson, N. et al. Building a global alliance of biofoundries. Nat. Commun. 10, 2040 (2019).","journal-title":"Nat. Commun."},{"key":"618_CR63","doi-asserted-by":"crossref","unstructured":"Arnold, C. Cloud labs: where robots do the research. Nature 606, 612\u2013613 (2022).","DOI":"10.1038\/d41586-022-01618-x"},{"key":"618_CR64","doi-asserted-by":"crossref","unstructured":"Segal, M. An operating system for the biology lab. Nature 573, S112\u2013S113 (2019).","DOI":"10.1038\/d41586-019-02875-z"},{"key":"618_CR65","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.3390\/ijms20082033","volume":"20","author":"CS Thiel","year":"2019","unstructured":"Thiel, C. S. et al. Real-time 3D high-resolution microscopy of human cells on the International Space Station. Int. J. Mol. Sci. 20, 2033 (2019).","journal-title":"Int. J. Mol. Sci."},{"key":"618_CR66","doi-asserted-by":"crossref","unstructured":"Ferl, R. J. & Paul, A.-L. The effect of spaceflight on the gravity-sensing auxin gradient of roots: GFP reporter gene microscopy on orbit. NPJ Microgravity 2, 15023 (2016).","DOI":"10.1038\/npjmgrav.2015.23"},{"key":"618_CR67","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1038\/s41587-021-01094-0","volume":"40","author":"NF Greenwald","year":"2022","unstructured":"Greenwald, N. F. et al. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat. Biotechnol. 40, 555\u2013565 (2022).","journal-title":"Nat. Biotechnol."},{"key":"618_CR68","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-40789-y","volume":"9","author":"AE Ronca","year":"2019","unstructured":"Ronca, A. E. et al. Behavior of mice aboard the International Space Station. Sci. Rep. 9, 4717 (2019).","journal-title":"Sci. Rep."},{"key":"618_CR69","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1016\/j.neuron.2015.11.031","volume":"88","author":"AB Wiltschko","year":"2015","unstructured":"Wiltschko, A. B. et al. Mapping sub-second structure in mouse behavior. Neuron 88, 1121\u20131135 (2015).","journal-title":"Neuron"},{"key":"618_CR70","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1038\/s41592-021-01106-6","volume":"18","author":"TW Dunn","year":"2021","unstructured":"Dunn, T. W. et al. Geometric deep learning enables 3D kinematic profiling across species and environments. Nat. Methods 18, 564\u2013573 (2021).","journal-title":"Nat. Methods"},{"key":"618_CR71","doi-asserted-by":"crossref","unstructured":"Pereira, T. D. et al. SLEAP: A deep learning system for multi-animal pose tracking. Nat. Methods 19, 486\u2013495 (2022).","DOI":"10.1038\/s41592-022-01426-1"},{"key":"618_CR72","doi-asserted-by":"crossref","unstructured":"Mathis, A. et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21, 1281\u20131289 (2018).","DOI":"10.1038\/s41593-018-0209-y"},{"key":"618_CR73","doi-asserted-by":"crossref","unstructured":"Zhang, P. et al. Multi-scale vision longformer: A new vision transformer for high-resolution image encoding. In Proc. IEEE\/CVF Intl. Conf. Computer Vision 2998\u20133008 (2021).","DOI":"10.1109\/ICCV48922.2021.00299"},{"key":"618_CR74","doi-asserted-by":"crossref","unstructured":"Chen, Z. et al. Visformer: The vision-friendly transformer. In Proc. IEEE\/CVF Intl. Conf. Computer Vision 589\u2013598 (2021).","DOI":"10.1109\/ICCV48922.2021.00063"},{"key":"618_CR75","unstructured":"Savoy, M. IDx-DR for Diabetic Retinopathy Screening. American Family Physician https:\/\/www.aafp.org\/afp\/2020\/0301\/p307.html (2020)."},{"key":"618_CR76","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1167\/iovs.61.14.34","volume":"61","author":"RJ Vyas","year":"2020","unstructured":"Vyas, R. J. et al. Decreased vascular patterning in the retinas of astronaut crew members as new measure of ocular damage in spaceflight-associated neuro-ocular syndrome. Invest. Ophthalmol. Vis. Sci. 61, 34 (2020).","journal-title":"Invest. Ophthalmol. Vis. Sci."},{"key":"618_CR77","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1159\/000514211","volume":"58","author":"M Lagatuz","year":"2021","unstructured":"Lagatuz, M. et al. Vascular patterning as integrative readout of complex molecular and physiological signaling by VESsel GENeration analysis. J. Vasc. Res. 58, 207\u2013230 (2021).","journal-title":"J. Vasc. Res."},{"key":"618_CR78","doi-asserted-by":"crossref","unstructured":"Lee, A. G. et al. Spaceflight associated neuro-ocular syndrome (SANS) and the neuro-ophthalmologic effects of microgravity: a review and an update. NPJ Microgravity 6, 7 (2020).","DOI":"10.1038\/s41526-020-0097-9"},{"key":"618_CR79","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1038\/s41433-020-01263-6","volume":"35","author":"R Chopra","year":"2021","unstructured":"Chopra, R., Wagner, S. K. & Keane, P. A. Optical coherence tomography in the 2020s-outside the eye clinic. Eye 35, 236\u2013243 (2021).","journal-title":"Eye"},{"key":"618_CR80","doi-asserted-by":"publisher","first-page":"1096","DOI":"10.21037\/atm-20-4355","volume":"8","author":"I Sher","year":"2020","unstructured":"Sher, I., Moverman, D., Ketter-Katz, H., Moisseiev, E. & Rotenstreich, Y. In vivo retinal imaging in translational regenerative research. Ann. Transl. Med. 8, 1096 (2020).","journal-title":"Ann. Transl. Med."},{"key":"618_CR81","doi-asserted-by":"publisher","first-page":"2546","DOI":"10.3390\/ijms19092546","volume":"19","author":"XW Mao","year":"2018","unstructured":"Mao, X. W. et al. Impact of spaceflight and artificial gravity on the mouse retina: biochemical and proteomic analysis. Int. J. Mol. Sci. 19, 2546 (2018).","journal-title":"Int. J. Mol. Sci."},{"key":"618_CR82","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-18364-0","volume":"7","author":"SL Castro-Wallace","year":"2017","unstructured":"Castro-Wallace, S. L. et al. Nanopore DNA sequencing and genome assembly on the International Space Station. Sci. Rep. 7, 18022 (2017).","journal-title":"Sci. Rep."},{"key":"618_CR83","doi-asserted-by":"crossref","unstructured":"McIntyre, A. B. R. et al. Nanopore sequencing in microgravity. NPJ Microgravity 2, 16035 (2016).","DOI":"10.1038\/npjmgrav.2016.35"},{"key":"618_CR84","doi-asserted-by":"publisher","first-page":"106","DOI":"10.3390\/genes12010106","volume":"12","author":"S Stahl-Rommel","year":"2021","unstructured":"Stahl-Rommel, S. et al. Real-time culture-independent microbial profiling onboard the International Space Station using nanopore sequencing. Genes 12, 106 (2021).","journal-title":"Genes"},{"key":"618_CR85","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.trechm.2019.02.007","volume":"1","author":"F H\u00e4se","year":"2019","unstructured":"H\u00e4se, F., Roch, L. M. & Aspuru-Guzik, A. Next-generation experimentation with self-driving laboratories. Trends Chem. 1, 282\u2013291 (2019).","journal-title":"Trends Chem."},{"key":"618_CR86","doi-asserted-by":"crossref","unstructured":"Garcia Martin, H. et al. Perspectives for self-driving labs in synthetic biology. Curr. Opin. Biotech. 79, 102881 (2023).","DOI":"10.1016\/j.copbio.2022.102881"},{"key":"618_CR87","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-15798-5","volume":"11","author":"O Borkowski","year":"2020","unstructured":"Borkowski, O. et al. Large scale active-learning-guided exploration for in vitro protein production optimization. Nat. Commun. 11, 1872 (2020).","journal-title":"Nat. Commun."},{"key":"618_CR88","doi-asserted-by":"crossref","unstructured":"Kitano, H. Nobel Turing Challenge: creating the engine for scientific discovery. NPJ Syst. Biol. Appl. 7, 29 (2021).","DOI":"10.1038\/s41540-021-00189-3"},{"key":"618_CR89","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1038\/s42004-021-00550-x","volume":"4","author":"M Christensen","year":"2021","unstructured":"Christensen, M. et al. Data-science driven autonomous process optimization. Commun. Chem. 4, 112 (2021).","journal-title":"Commun. Chem."},{"key":"618_CR90","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1038\/s41586-018-0307-8","volume":"559","author":"JM Granda","year":"2018","unstructured":"Granda, J. M., Donina, L., Dragone, V., Long, D.-L. & Cronin, L. Controlling an organic synthesis robot with machine learning to search for new reactivity. Nature 559, 377\u2013381 (2018).","journal-title":"Nature"},{"key":"618_CR91","doi-asserted-by":"publisher","first-page":"eaaz8867","DOI":"10.1126\/sciadv.aaz8867","volume":"6","author":"BP MacLeod","year":"2020","unstructured":"MacLeod, B. P. et al. Self-driving laboratory for accelerated discovery of thin-film materials. Sci. Adv. 6, eaaz8867 (2020).","journal-title":"Sci. Adv."},{"key":"618_CR92","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-19597-w","volume":"11","author":"AG Kusne","year":"2020","unstructured":"Kusne, A. G. et al. On-the-fly closed-loop materials discovery via Bayesian active learning. Nat. Commun. 11, 5966 (2020).","journal-title":"Nat. Commun."},{"key":"618_CR93","doi-asserted-by":"publisher","first-page":"1474","DOI":"10.1021\/acssynbio.8b00540","volume":"8","author":"P Carbonell","year":"2019","unstructured":"Carbonell, P., Radivojevic, T. & Mart\u00edn, H. G. Opportunities at the intersection of synthetic biology, machine learning, and automation. ACS Synth. Biol. 8, 1474\u20131477 (2019).","journal-title":"ACS Synth. Biol."},{"key":"618_CR94","doi-asserted-by":"publisher","first-page":"1151","DOI":"10.1021\/acssynbio.5b00062","volume":"4","author":"SCC Shih","year":"2015","unstructured":"Shih, S. C. C. et al. A versatile microfluidic device for automating synthetic biology. ACS Synth. Biol. 4, 1151\u20131164 (2015).","journal-title":"ACS Synth. Biol."},{"key":"618_CR95","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1039\/C4LC00794H","volume":"15","author":"SCC Shih","year":"2015","unstructured":"Shih, S. C. C. et al. A droplet-to-digital (D2D) microfluidic device for single cell assays. Lab Chip 15, 225\u2013236 (2015).","journal-title":"Lab Chip"},{"key":"618_CR96","doi-asserted-by":"crossref","unstructured":"Iwai, K. et al. Scalable and automated CRISPR-based strain engineering using droplet microfluidics. Microsys. Nanoeng. 8, 31 (2022).","DOI":"10.1038\/s41378-022-00357-3"},{"key":"618_CR97","doi-asserted-by":"publisher","first-page":"eabf8761","DOI":"10.1126\/science.abf8761","volume":"373","author":"CJ Markin","year":"2021","unstructured":"Markin, C. J. et al. Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics. Science 373, eabf8761 (2021).","journal-title":"Science"},{"key":"618_CR98","doi-asserted-by":"publisher","first-page":"1509","DOI":"10.1039\/b927258e","volume":"10","author":"MM Crane","year":"2010","unstructured":"Crane, M. M., Chung, K., Stirman, J. & Lu, H. Microfluidics-enabled phenotyping, imaging, and screening of multicellular organisms. Lab Chip 10, 1509\u20131517 (2010).","journal-title":"Lab Chip"},{"key":"618_CR99","unstructured":"Nakai, M. & Ke, W. Review of the methods for handling missing data in longitudinal data analysis. Int. J. Math. Analysis 5, 1\u201313 (2011)."},{"key":"618_CR100","doi-asserted-by":"publisher","first-page":"1753","DOI":"10.1093\/bioinformatics\/bty884","volume":"35","author":"S Ray","year":"2019","unstructured":"Ray, S. et al. GeneLab: omics database for spaceflight experiments. Bioinformatics 35, 1753\u20131759 (2019).","journal-title":"Bioinformatics"},{"key":"618_CR101","doi-asserted-by":"publisher","first-page":"D1515","DOI":"10.1093\/nar\/gkaa887","volume":"49","author":"DC Berrios","year":"2021","unstructured":"Berrios, D. C., Galazka, J., Grigorev, K., Gebre, S. & Costes, S. V. NASA GeneLab: interfaces for the exploration of space omics data. Nucleic Acids Res. 49, D1515\u2013D1522 (2021).","journal-title":"Nucleic Acids Res."},{"key":"618_CR102","doi-asserted-by":"publisher","first-page":"108441","DOI":"10.1016\/j.celrep.2020.108441","volume":"33","author":"RT Scott","year":"2020","unstructured":"Scott, R. T. et al. Advancing the integration of biosciences data sharing to further enable space exploration. Cell Rep. 33, 108441 (2020).","journal-title":"Cell Rep."},{"key":"618_CR103","unstructured":"Sanders, L. M. & Costes, S. V. NASA Science Mission Directorate Artificial Intelligence Workshop Report: Standards for AI readiness. National Aeronautics and Space Administration 22\u201329 (NASA, 2021)."},{"key":"618_CR104","doi-asserted-by":"publisher","first-page":"E14","DOI":"10.1038\/s41586-020-2766-y","volume":"586","author":"B Haibe-Kains","year":"2020","unstructured":"Haibe-Kains, B. et al. Transparency and reproducibility in artificial intelligence. Nature 586, E14\u2013E16 (2020).","journal-title":"Nature"},{"key":"618_CR105","doi-asserted-by":"crossref","unstructured":"Gebru, T. et al. Datasheets for datasets. Comms. ACM 64, 86\u201392 (2021).","DOI":"10.1145\/3458723"},{"key":"618_CR106","doi-asserted-by":"publisher","first-page":"D347","DOI":"10.1093\/nar\/gkw918","volume":"45","author":"E Ong","year":"2017","unstructured":"Ong, E. et al. Ontobee: a linked ontology data server to support ontology term dereferencing, linkage, query and integration. Nucleic Acids Res. 45, D347\u2013D352 (2017).","journal-title":"Nucleic Acids Res."},{"key":"618_CR107","doi-asserted-by":"publisher","first-page":"W170","DOI":"10.1093\/nar\/gkp440","volume":"37","author":"NF Noy","year":"2009","unstructured":"Noy, N. F. et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res. 37, W170\u2013W173 (2009).","journal-title":"Nucleic Acids Res."},{"key":"618_CR108","doi-asserted-by":"publisher","first-page":"D966","DOI":"10.1093\/nar\/gkt1026","volume":"42","author":"S K\u00f6hler","year":"2014","unstructured":"K\u00f6hler, S. et al. The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. 42, D966\u2013D974 (2014).","journal-title":"Nucleic Acids Res."},{"key":"618_CR109","unstructured":"Radiation biology ontology. BioPortal https:\/\/bioportal.bioontology.org\/ontologies\/RBO (2022)."},{"key":"618_CR110","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1038\/d41586-018-05895-3","volume":"560","author":"R Kwok","year":"2018","unstructured":"Kwok, R. How to pick an electronic laboratory notebook. Nature 560, 269\u2013270 (2018).","journal-title":"Nature"},{"key":"618_CR111","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1186\/s13321-017-0221-3","volume":"9","author":"S Kanza","year":"2017","unstructured":"Kanza, S. et al. Electronic lab notebooks: can they replace paper? J. Cheminform. 9, 31 (2017).","journal-title":"J. Cheminform."},{"key":"618_CR112","doi-asserted-by":"crossref","unstructured":"Erard, S. et al. VESPA: a community-driven Virtual Observatory in Planetary Science. Planetary and Space Science 150, 65\u201385 (2018).","DOI":"10.1016\/j.pss.2017.05.013"},{"key":"618_CR113","unstructured":"Zaslavsky, I. et al. EarthCube Data Discovery Hub: enhancing, curating and finding data across multiple geoscience data sources. American Geophysical Union, Fall Meeting 2017 Abstract IN21B-0049 (American Geophysical Union, 2017)."},{"key":"618_CR114","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1016\/j.ccell.2020.09.006","volume":"38","author":"DJ Crichton","year":"2020","unstructured":"Crichton, D. J. et al. Cancer biomarkers and big data: a planetary science approach. Cancer Cell 38, 757\u2013760 (2020).","journal-title":"Cancer Cell"},{"key":"618_CR115","doi-asserted-by":"crossref","unstructured":"Greene, G., Plante, R. & Hanisch, R. Building open access to research (OAR) data infrastructure at NIST. Data Sci. J. 18, 10.5334\/dsj-2019-030 (2019).","DOI":"10.5334\/dsj-2019-030"},{"key":"618_CR116","doi-asserted-by":"crossref","unstructured":"McGregor, C. A platform for real-time space health analytics as a service utilizing space data relays. In 2021 IEEE Aerospace Conference (50100) 1\u201314 (IEEE, 2021).","DOI":"10.1109\/AERO50100.2021.9438475"},{"key":"618_CR117","doi-asserted-by":"crossref","unstructured":"McGregor, C. A platform for real-time online health analytics during spaceflight. In 2013 IEEE Aerospace Conference 1\u20138 (IEEE, 2013).","DOI":"10.1109\/AERO.2013.6497382"},{"key":"618_CR118","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-33128-9","volume":"13","author":"A Lavin","year":"2022","unstructured":"Lavin, A. et al. Technology readiness levels for machine learning systems. Nat. Commun. 13, 6039 (2022).","journal-title":"Nat. Commun."},{"key":"618_CR119","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1038\/s41592-021-01256-7","volume":"18","author":"BJ Heil","year":"2021","unstructured":"Heil, B. J. et al. Reproducibility standards for machine learning in the life sciences. Nat. Methods 18, 1132\u20131135 (2021).","journal-title":"Nat. Methods"},{"key":"618_CR120","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1093\/bib\/bbaa012","volume":"22","author":"SK Mohamed","year":"2021","unstructured":"Mohamed, S. K., Nounu, A. & Nov\u00e1\u010dek, V. Biological applications of knowledge graph embedding models. Brief. Bioinform. 22, 1679\u20131693 (2021).","journal-title":"Brief. Bioinform."},{"key":"618_CR121","unstructured":"Ehrlinger, L. & W\u00f6\u00df, W. Towards a definition of knowledge graphs. SEMANTICS 2016 Posters and Demos Track 1\u20134 (SEMANTICS, 2016)."},{"key":"618_CR122","doi-asserted-by":"publisher","first-page":"42","DOI":"10.3390\/life11010042","volume":"11","author":"CA Nelson","year":"2021","unstructured":"Nelson, C. A. et al. Knowledge network embedding of transcriptomic data from spaceflown mice uncovers signs and symptoms associated with terrestrial diseases. Life 11, 42 (2021).","journal-title":"Life"},{"key":"618_CR123","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11069-0","volume":"10","author":"CA Nelson","year":"2019","unstructured":"Nelson, C. A., Butte, A. J. & Baranzini, S. E. Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings. Nat. Commun. 10, 3045 (2019).","journal-title":"Nat. Commun."},{"key":"618_CR124","doi-asserted-by":"crossref","unstructured":"Nelson, C. A., Bove, R., Butte, A. J. & Baranzini, S. E. Embedding electronic health records onto a knowledge network recognizes prodromal features of multiple sclerosis and predicts diagnosis. J. Am. Med. Inform. Assoc. 29, 424\u2013434 (2021).","DOI":"10.1093\/jamia\/ocab270"},{"key":"618_CR125","unstructured":"Antonsen, E. L. et al. Directed acyclic graph guidance documentation. NASA Technical Reports Server (NASA, 2022)."},{"key":"618_CR126","doi-asserted-by":"publisher","first-page":"2187","DOI":"10.3390\/biomedicines10092187","volume":"10","author":"RJ Reynolds","year":"2022","unstructured":"Reynolds, R. J. et al. Validating causal diagrams of human health risks for spaceflight: an example using bone data from rodents. Biomedicines 10, 2187 (2022).","journal-title":"Biomedicines"},{"key":"618_CR127","unstructured":"Pawar, U., O\u2019Shea, D., Rea, S. & O\u2019Reilly, R. Incorporating explainable artificial intelligence (XAI) to aid the understanding of machine learning in the healthcare domain. in Proc. Artif. Intell. Cogn. Sci. 169\u2013180 (2020)."},{"key":"618_CR128","doi-asserted-by":"crossref","unstructured":"Adadi, A. & Berrada, M. in Embedded Systems and Artificial Intelligence (ed. Ditzinger, T.) 327\u2013337 (Springer Singapore, 2020).","DOI":"10.1007\/978-981-15-0947-6_31"},{"key":"618_CR129","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.inffus.2021.07.016","volume":"77","author":"G Yang","year":"2022","unstructured":"Yang, G., Ye, Q. & Xia, J. Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: a mini-review, two showcases and beyond. Inf. Fusion 77, 29\u201352 (2022).","journal-title":"Inf. Fusion"},{"key":"618_CR130","first-page":"502","volume":"281","author":"E Rajabi","year":"2021","unstructured":"Rajabi, E. & Etminani, K. Towards a knowledge graph-based explainable decision support system in healthcare. Stud. Health Technol. Inform. 281, 502\u2013503 (2021).","journal-title":"Stud. Health Technol. Inform."},{"key":"618_CR131","first-page":"1","volume":"22","author":"I Covert","year":"2021","unstructured":"Covert, I., Lundberg, S. & Lee, S.-I. Explaining by removing: a unified framework for model explanation. J. Mach. Learn. Res. 22, 1\u201390 (2021).","journal-title":"J. Mach. Learn. Res."},{"key":"618_CR132","doi-asserted-by":"crossref","unstructured":"Ribeiro, M. T., Singh, S. & Guestrin, C. \u2018Why should I trust you?\u2019: Explaining the predictions of any classifier. Preprint at https:\/\/arxiv.org\/abs\/1602.04938 (2016).","DOI":"10.1145\/2939672.2939778"},{"key":"618_CR133","unstructured":"Lundberg, S. & Lee, S.-I. A unified approach to interpreting model predictions. Preprint at https:\/\/arxiv.org\/abs\/1705.07874 (2017)."},{"key":"618_CR134","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow, I. et al. Generative adversarial networks. Commun. ACM 63, 139\u2013144 (2020).","journal-title":"Commun. ACM"},{"key":"618_CR135","unstructured":"Kingma, D. P. & Welling, M. Auto-encoding variational Bayes. Preprint at https:\/\/arxiv.org\/abs\/1312.6114 (2013)."},{"key":"618_CR136","unstructured":"Antoniadou, E. et al. NASA frontier development lab technical memorandum: harnessing AI to support medical care in space. Frontier Development Lab (Frontier Development Lab, 2019)."},{"key":"618_CR137","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1038\/s42256-019-0017-4","volume":"1","author":"A Gupta","year":"2019","unstructured":"Gupta, A. & Zou, J. Feedback GAN for DNA optimizes protein functions. Nat. Mach. Intell. 1, 105\u2013111 (2019).","journal-title":"Nat. Mach. Intell."},{"key":"618_CR138","doi-asserted-by":"crossref","unstructured":"Vi\u00f1as, R., Andr\u00e9s-Terr\u00e9, H., Li\u00f2, P. & Bryson, K. Adversarial generation of gene expression data. Bioinformatics 38, 730-737 (2021).","DOI":"10.1093\/bioinformatics\/btab035"},{"key":"618_CR139","doi-asserted-by":"crossref","unstructured":"Ghimire, S. et al. Generative modeling and inverse imaging of cardiac transmembrane potential. In Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2018 508\u2013516 (Springer, 2018).","DOI":"10.1007\/978-3-030-00934-2_57"},{"key":"618_CR140","unstructured":"Shakeri, F. et al. FHIST: a benchmark for few-shot classification of histological images. Preprint at https:\/\/arxiv.org\/abs\/2206.00092 (2022)."},{"key":"618_CR141","unstructured":"Yang, J., Chen, H., Yan, J., Chen, X. & Yao, J. Towards better understanding and better generalization of few-shot classification in histology images with contrastive learning. Preprint at https:\/\/arxiv.org\/abs\/2202.09059 (2022)."},{"key":"618_CR142","doi-asserted-by":"crossref","unstructured":"Ravishankar, H. et al. in Deep Learning and Data Labeling for Medical Applications (eds. Carneiro, G. et al.) 188\u2013196 (Springer, 2016).","DOI":"10.1007\/978-3-319-46976-8_20"},{"key":"618_CR143","doi-asserted-by":"publisher","first-page":"14037","DOI":"10.1007\/s00521-021-06044-0","volume":"33","author":"F Altaf","year":"2021","unstructured":"Altaf, F., Islam, S. M. S. & Janjua, N. K. A novel augmented deep transfer learning for classification of COVID-19 and other thoracic diseases from X-rays. Neural Comput. Appl. 33, 14037\u201314048 (2021).","journal-title":"Neural Comput. Appl."},{"key":"618_CR144","unstructured":"Bersuker, G., Mason, M. & Jones, K. L. Neuromorphic computing: the potential for high-performance processing in space. Center for Space Policy and Strategy https:\/\/csps.aerospace.org\/sites\/default\/files\/2021-08\/Bersuker_NeuromorphicComputing_12132018.pdf (The Aerospace Corporation, 2018)."},{"key":"618_CR145","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/MM.2018.112130359","volume":"38","author":"M Davies","year":"2018","unstructured":"Davies, M. et al. Loihi: a neuromorphic manycore processor with on-chip learning. IEEE Micro 38, 82\u201399 (2018).","journal-title":"IEEE Micro"},{"key":"618_CR146","doi-asserted-by":"publisher","first-page":"823","DOI":"10.1038\/s42256-021-00388-x","volume":"3","author":"J G\u00f6ltz","year":"2021","unstructured":"G\u00f6ltz, J. et al. Fast and energy-efficient neuromorphic deep learning with first-spike times. Nat. Mach. Intell. 3, 823\u2013835 (2021).","journal-title":"Nat. Mach. Intell."},{"key":"618_CR147","doi-asserted-by":"crossref","unstructured":"Dahl, S. G., Ivans, R. C. & Cantley, K. D. Learning behavior of memristor-based neuromorphic circuits in the presence of radiation. Proc. Intl. Conf. Neuromorphic Syst. 53\u201356 (ACM, 2019).","DOI":"10.1145\/3354265.3354272"},{"key":"618_CR148","doi-asserted-by":"crossref","unstructured":"Yanguas-Gil, A. et al. Neuromorphic architectures for edge computing under extreme environments. 2021 IEEE Space Computing Conference (SCC) 39\u201345 (2021).","DOI":"10.1109\/SCC49971.2021.00012"},{"key":"618_CR149","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1038\/s41586-022-04992-8","volume":"608","author":"W Wan","year":"2022","unstructured":"Wan, W. et al. A compute-in-memory chip based on resistive random-access memory. Nature 608, 504\u2013512 (2022).","journal-title":"Nature"},{"key":"618_CR150","doi-asserted-by":"crossref","unstructured":"Furano, G. et al. Towards the use of artificial intelligence on the edge in space systems: challenges and opportunities. IEEE Aerospace Electron Syst. Mag. 35, 44\u201356 (2020).","DOI":"10.1109\/MAES.2020.3008468"},{"key":"618_CR151","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-32550-3","volume":"13","author":"MC Caro","year":"2022","unstructured":"Caro, M. C. et al. Generalization in quantum machine learning from few training data. Nat. Commun. 13, 4919 (2022).","journal-title":"Nat. Commun."},{"key":"618_CR152","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-22539-9","volume":"12","author":"H-Y Huang","year":"2021","unstructured":"Huang, H.-Y. et al. Power of data in quantum machine learning. Nat. Commun. 12, 2631 (2021).","journal-title":"Nat. Commun."},{"key":"618_CR153","unstructured":"Farhi, E. & Neven, H. Classification with quantum neural networks on near term processors. Preprint at https:\/\/arxiv.org\/abs\/1802.06002 (2018)."},{"key":"618_CR154","unstructured":"Quenelle, N. NASA TechLeap Prize winner tests quantum earth observation system. NASA Feature https:\/\/www.nasa.gov\/feature\/nasa-techleap-prize-winner-tests-quantum-earth-observation-system (NASA, 2022)."},{"key":"618_CR155","doi-asserted-by":"publisher","first-page":"20190101","DOI":"10.1098\/rsfs.2019.0101","volume":"10","author":"EU Hammarlund","year":"2020","unstructured":"Hammarlund, E. U. Harnessing hypoxia as an evolutionary driver of complex multicellularity. Interface Focus 10, 20190101 (2020).","journal-title":"Interface Focus"},{"key":"618_CR156","doi-asserted-by":"publisher","first-page":"1287","DOI":"10.1109\/TNNLS.2017.2673021","volume":"29","author":"J Liu","year":"2018","unstructured":"Liu, J., Harkin, J., Maguire, L. P., McDaid, L. J. & Wade, J. J. SPANNER: a self-repairing spiking neural network hardware architecture. IEEE Trans. Neural Netw. Learn. Syst. 29, 1287\u20131300 (2018).","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"618_CR157","unstructured":"Leino, K. et al. Self-correcting neural networks for safe classification. Preprint at https:\/\/arxiv.org\/abs\/2107.11445 (2021)."},{"key":"618_CR158","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-21770-8","volume":"12","author":"C Ruiz","year":"2021","unstructured":"Ruiz, C., Zitnik, M. & Leskovec, J. Identification of disease treatment mechanisms through the multiscale interactome. Nat. Commun. 12, 1796 (2021).","journal-title":"Nat. Commun."},{"key":"618_CR159","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1016\/j.cels.2021.05.012","volume":"12","author":"LV Schaffer","year":"2021","unstructured":"Schaffer, L. V. & Ideker, T. Mapping the multiscale structure of biological systems. Cell Syst. 12, 622\u2013635 (2021).","journal-title":"Cell Syst"},{"key":"618_CR160","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.cels.2016.02.003","volume":"2","author":"MK Yu","year":"2016","unstructured":"Yu, M. K. et al. Translation of genotype to phenotype by a hierarchy of cell subsystems. Cell Syst. 2, 77\u201388 (2016).","journal-title":"Cell Syst."},{"key":"618_CR161","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.cell.2012.05.044","volume":"150","author":"JR Karr","year":"2012","unstructured":"Karr, J. R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150, 389\u2013401 (2012).","journal-title":"Cell"},{"key":"618_CR162","doi-asserted-by":"publisher","first-page":"eaav3751","DOI":"10.1126\/science.aav3751","volume":"369","author":"DN Macklin","year":"2020","unstructured":"Macklin, D. N. et al. Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation. Science 369, eaav3751 (2020).","journal-title":"Science"},{"key":"618_CR163","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1038\/nrm1054","volume":"4","author":"PJ Hunter","year":"2003","unstructured":"Hunter, P. J. & Borg, T. K. Integration from proteins to organs: the Physiome Project. Nat. Rev. Mol. Cell Biol. 4, 237\u2013243 (2003).","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"618_CR164","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.pbiomolbio.2010.03.002","volume":"104","author":"M Fink","year":"2011","unstructured":"Fink, M. et al. Cardiac cell modelling: observations from the heart of the cardiac Physiome Project. Prog. Biophys. Mol. Biol. 104, 2\u201321 (2011).","journal-title":"Prog. Biophys. Mol. Biol."},{"key":"618_CR165","unstructured":"Space Station Research Explorer. NASA https:\/\/www.nasa.gov\/mission_pages\/station\/research\/experiments\/explorer\/ (accessed 1 October 2022)."},{"key":"618_CR166","first-page":"50","volume":"37","author":"T Li","year":"2020","unstructured":"Li, T., Sahu, A. K., Talwalkar, A. & Smith, V. Federated learning: challenges, methods, and future directions. IEEE Signal Process. Mag. 37, 50\u201360 (2020).","journal-title":"IEEE Signal Process. Mag."},{"key":"618_CR167","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1109\/MC.2016.145","volume":"49","author":"W Shi","year":"2016","unstructured":"Shi, W. & Dustdar, S. The promise of edge computing. Computer 49, 78\u201381 (2016).","journal-title":"Computer"}],"container-title":["Nature Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s42256-023-00618-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-023-00618-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-023-00618-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,23]],"date-time":"2023-03-23T17:08:41Z","timestamp":1679591321000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s42256-023-00618-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,23]]},"references-count":167,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["618"],"URL":"https:\/\/doi.org\/10.1038\/s42256-023-00618-4","relation":{},"ISSN":["2522-5839"],"issn-type":[{"value":"2522-5839","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,23]]},"assertion":[{"value":"23 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 March 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}