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The cutting edge of applying AI to science is the closed-loop automation of scientific research: robot scientists.
Princeton University Press, 1991
P. M. M. Duhem, The Aim and Structure of Physical Theory · 1991
Earlier work this paper cites.
R. D. King, K. E. Whelan, F. M. Jones, P. G. K. Reiser, C. H. Bryant, S. H. Muggleton, D. B. Kell, and S. G. Oliver, “Functional genomic hypothesis generation and experimentation by a robot scientist,” Nature
2004
Earlier work this paper cites.
K. Korovin, “iProver – an instantiation-based theorem prover for first-order logic (system description),” in Automated Reasoning
2008
Earlier work this paper cites.
R. D. King, J. Rowland, S. G. Oliver, M. Young, W. Aubrey, E. Byrne, M. Liakata, M. Markham, P. Pir, L. N. Soldatova, A. Sparkes, K. E. Whelan, and A. Clare, “The automation of science,” Science
2009
Earlier work this paper cites.
E. Bilsland, A. Sparkes, K. Williams, H. J. Moss, M. de Clare, P. Pir, J. Rowland, W. Aubrey, R. Pateman, M. Young, M. Carrington, R. D. King, and S. G. Oliver, “Yeast-based automated high-throughput screens to identify anti-parasitic lead compounds,” Open Biology
2013
Earlier work this paper cites.
Publisher: Royal Society
K. Williams, E. Bilsland, A. Sparkes, W. Aubrey, M. Young, L. N. Soldatova, K. De Grave, J. Ramon, M. de Clare, W. Sirawaraporn, S. G. Oliver, and R. D. King, “Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases,” Journal of The Royal Society Interface · 2015
Earlier work this paper cites.
E. Bilsland, L. van Vliet, K. Williams, J. Feltham, M. P. Carrasco, W. L. Fotoran, E. F. G. Cubillos, G. Wunderlich, M. Grøtli, F. Hollfelder, V. Jackson, R. D. King, and S. G. Oliver, “Plasmodium dihydrofolate reductase is a second enzyme target for the antimalarial action of triclosan,” Scientific Reports
2018
Cited alongside, same era.
A. Coutant, K. Roper, D. Trejo-Banos, D. Bouthinon, M. Carpenter, J. Grzebyta, G. Santini, H. Soldano, M. Elati, J. Ramon, C. Rouveirol, L. N. Soldatova, and R. D. King, “Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast,” Proceedings of the National Academy of Sciences
2019
Cited alongside, same era.
H. Kitano, “Nobel turing challenge: creating the engine for scientific discovery,” npj Systems Biology and Applications
2021
Cited alongside, same era.
R. King and H. Zenil, “Artificial intelligence in scientific discovery: Challenges and opportunities,” tech. rep., OECD, 2023
2023
G. K. Reder, A. H. Gower, F. Kronström, R. Halle, V. Mahamuni, A. Patel, H. Hayatnagarkar, L. N. Soldatova, and R. D. King, “Genesis-DB: a database for autonomous laboratory systems,” Bioinformatics Advances
2023
Later among the works it cites.
F. Kronström, A. H. Gower, I. A. Tiukova, and R. D. King, “RIMBO - an ontology for model revision databases,” in Discovery Science
2023
Later among the works it cites.
D. Brunnsåker, G. K. Reder, N. K. Soni, O. I. Savolainen, A. H. Gower, I. A. Tiukova, and R. D. King, “High-throughput metabolomics for the design and validation of a diauxic shift model,” npj Systems Biology and Applications
2023
Later among the works it cites.
A. H. Gower, K. Korovin, D. Brunnsåker, I. A. Tiukova, and R. D. King, “LGEM+: A first-order logic framework for automated improvement of metabolic network models through abduction,” in Discovery Science
2023
Later among the works it cites.
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Cited alongside, same era.
R. King and H. Zenil, “A framework for evaluating the AI-driven automation of science,” tech. rep., OECD, 2023
2023
Cited alongside, same era.
R. King, O. Peter, and P. Courtney, “Robot scientists: From Adam to Eve to Genesis,” tech. rep., OECD, 2023
2023
Cited alongside, same era.
G. K. Reder, E. Y. Bjurström, D. Brunnsåker, F. Kronström, P. Lasin, I. Tiukova, O. I. Savolainen, J. N. Dodds, J. C. May, J. P. Wikswo, J. A. McLean, and R. D. King, “AutonoMS: Automated ion mobility metabolomic fingerprinting,” Journal of the American Society for Mass Spectrometry
2024
Closest in time.
D. Brunnsåker, F. Kronström, I. A. Tiukova, and R. D. King, “Interpreting protein abundance in Saccharomyces cerevisiae through relational learning,” Bioinformatics
2024
Closest in time.