The DOI matches its Crossref record; 66 of the 67 references it cites were found in a registry or an index, and 1 are not checked yet.
Functional genomic hypothesis generation and experimentation by a robot scientist
Open accessAbstract
The question of whether it is possible to automate the scientific process is of both great theoretical interest and increasing practical importance because, in many scientific areas, data are being generated much faster than they can be effectively analysed. We describe a physically implemented robotic system that applies techniques from artificial intelligence to carry out cycles of scientific experimentation. The system automatically originates hypotheses to explain observations, devises experiments to test these hypotheses, physically runs the experiments using a laboratory robot, interprets the results to falsify hypotheses inconsistent with the data, and then repeats the cycle. Here we apply the system to the determination of gene function using deletion mutants of yeast (Saccharomyces cerevisiae) and auxotrophic growth experiments. We built and tested a detailed logical model (involving genes, proteins and metabolites) of the aromatic amino acid synthesis pathway. In biological experiments that automatically reconstruct parts of this model, we show that an intelligent experiment selection strategy is competitive with human performance and significantly outperforms, with a cost decrease of 3-fold and 100-fold (respectively), both cheapest and random-experiment selection.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Citations
Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Reflecting on reflexive thematic analysis
Braun, V., & Clarke, V. (2019) · Qualitative Research in Sport, Exercise and Health · doi:10.1080/2159676x.2019.1628806 · Cited by 19,677
Sample Size in Qualitative Interview Studies: Guided by Information Power
Malterud, K., Siersma, V. D., & Guassora, A. D. (2016) · Qualitative Health Research · doi:10.1177/1049732315617444 · Cited by 12,703
The Logic of Scientific Discovery
Jason, G. (1988) · Encyclopedia of Research Design · doi:10.4135/9781412961288.n223 · Cited by 9,743
The Logic of Scientific Discovery.
Hutchison, T. W., & Popper, K. R. (1959) · Economica · doi:10.2307/2550489 · Cited by 7,629
Hunter, D. J., & Bierma‐Zeinstra, S. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30417-9 · Cited by 5,127
Functional profiling of the Saccharomyces cerevisiae genome
Giaever, G., Chu, A. M., Ni, L., Connelly, C., Riles, L., Véronneau, S., Dow, S., Lucau-Danila, A., Anderson, K., André, B., et al. (2002) · Nature · doi:10.1038/nature00935 · Cited by 4,316
Brachmann, C. B., Davies, A., Cost, G. J., Caputo, E. M., Li, J., Hieter, P., & Boeke, J. D. (1998) · Yeast · doi:10.1002/(sici)1097-0061(19980130)14:2 · Cited by 3,418
Glyn-Jones, S., Palmer, A. J. R., Agricola, R., Price, A. J., Vincent, T. L., Weinans, H., & Carr, A. J. (2015) · The Lancet · doi:10.1016/s0140-6736(14)60802-3 · Cited by 3,151
Fedorov, V. V., Studden, W. J., & Klimko, E. M. (1972) · Cited by 2,057
Active Learning with Statistical Models
Cohn, D. A., Zoubin Ghahramani, A., & Jordan, M. I. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.295 · Cited by 2,054
Theory of Optimal Experiments.
Herzberg, A. M., Wynn, H. P., Fedorov, V. V., Studden, W. J., & Klimko, E. M. (1972) · Biometrika · doi:10.2307/2334826 · Cited by 1,896
Muggleton, S. (1995) · New Generation Computing · doi:10.1007/bf03037227 · Cited by 1,411
Self-citationFear-avoidance model of chronic musculoskeletal pain: 12 years on
Vlaeyen, J. W. S., & Linton, S. J. (2012) · Pain · doi:10.1016/j.pain.2011.12.009 · Cited by 1,281
Moving differently in pain: A new theory to explain the adaptation to pain
Hodges, P. W., & Tucker, K. J. (2010) · Pain · doi:10.1016/j.pain.2010.10.020 · Cited by 1,276
MIPS: a database for genomes and protein sequences
Mewes, H. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.37 · Cited by 1,268
Exercise for osteoarthritis of the knee
Fransen, M., McConnell, S., Harmer, A. R., van der Esch, M., Simić, M., & Bennell, K. L. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd004376.pub3 · Cited by 1,171
Whither the Future of Controlling Quantum Phenomena?
RABITZ, H. A., de Vivie‐Riedle, R., Motzkus, M., & Kompa, K. L. (2000) · Science · doi:10.1126/science.288.5467.824 · Cited by 1,150
Pat Langley, B., Simon, H. A., Bradshaw, G. L., & Żytkow, J. M. (1987) · The MIT Press eBooks · doi:10.7551/mitpress/5782.003.0013 · Cited by 1,098
Genetic Control of Biochemical Reactions in Neurospora
Beadle, G. W., & Tatum, E. L. (1941) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.27.11.499 · Cited by 1,062
Recent Updates of Diagnosis, Pathophysiology, and Treatment on Osteoarthritis of the Knee
Jang, S., Lee, K.-J., & Ju, J. H. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052619 · Cited by 879
The burden of OA-health services and economics
Leifer, V. P., Katz, J. N., & Losina, E. (2021) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2021.05.007 · Cited by 817
Scientific Discovery: Computational Explorations of the Creative Processes
Pat Langley, B., Simon, H. A., Bradshaw, G. L., & Żytkow, J. M. (1987) · Medical Entomology and Zoology · Cited by 802
MIPS: a database for genomes and protein sequences
Mewes, H. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.31 · Cited by 790
Moseley, G. L. (2003) · Journal of Pain · doi:10.1016/s1526-5900(03)00488-7 · Cited by 530
Knee joint kinematics, kinetics and muscle co-contraction in knee osteoarthritis patient gait
Heiden, T. L., Lloyd, D. G., & Ackland, T. R. (2009) · Clinical Biomechanics · doi:10.1016/j.clinbiomech.2009.08.005 · Cited by 514
Langley, P. (1995) · Medical Entomology and Zoology · Cited by 512
Goh, S. L., Persson, M. S. M., Stocks, J., Hou, Y., Lin, J., Hall, M. C., Doherty, M., & Zhang, W. (2019) · Annals of Physical and Rehabilitation Medicine · doi:10.1016/j.rehab.2019.04.006 · Cited by 503
Neuromuscular alterations during walking in persons with moderate knee osteoarthritis
Hubley‐Kozey, C. L., Deluzio, K. J., Landry, S. C., McNutt, J., & Stanish, W. D. (2005) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2005.07.014 · Cited by 481
Bunzli, S., O’Brien, P., Ayton, D., Dowsey, M. M., Gunn, J. M., Choong, P., & Manski-Nankervis, J.-A. E. (2019) · Clinical Orthopaedics and Related Research · doi:10.1097/corr.0000000000000784 · Cited by 469
Flach, P. A., & Kakas, A. C. (2000) · Applied logic series · doi:10.1007/978-94-017-0606-3 · Cited by 449
Experience of living with knee osteoarthritis: a systematic review of qualitative studies
Wallis, J. A., Taylor, N. F., Bunzli, S., & Shields, N. (2019) · BMJ Open · doi:10.1136/bmjopen-2019-030060 · Cited by 416
Hurley, M., Walsh, N. E., Mitchell, H., Nicholas, J. M., & Patel, A. K. (2011) · Arthritis Care & Research · doi:10.1002/acr.20642 · Cited by 414
Bennell, K. L., Ahamed, Y., Jull, G., Bryant, C., Hunt, M. A., Forbes, A. B., Kasza, J., Akram, M., Metcalf, B., Harris, A., et al. (2016) · Arthritis Care & Research · doi:10.1002/acr.22744 · Cited by 406
Self-citationJensen, M. P., Turner, J. A., & Romano, J. M. (2007) · Pain · doi:10.1016/j.pain.2006.12.007 · Cited by 393
Alexanders, J., Anderson, A., & Henderson, S. (2015) · Physiotherapy · doi:10.1016/j.physio.2014.03.008 · Cited by 389
Hodges, P. W., van den Hoorn, W., Wrigley, T. V., Hinman, R. S., Bowles, K., Cicuttini, F., Wang, Y., & Bennell, K. L. (2015) · Manual Therapy · doi:10.1016/j.math.2015.07.004 · Cited by 372
Chronic pain: A reformulation of the cognitive-behavioural model
Sharp, T. J. (2001) · Behaviour Research and Therapy · doi:10.1016/s0005-7967(00)00061-9 · Cited by 356
Driver, C., Kean, B., Oprescu, F., & Lovell, G. P. (2017) · Disability and Rehabilitation · doi:10.1080/09638288.2016.1223176 · Cited by 344
Alperstein, D., & Sharpe, L. (2016) · The Journal of Pain · doi:10.1016/j.jpain.2015.10.021 · Cited by 342
Roos, E. M., Grønne, D. T., Skou, S. T., Zywiel, M. G., McGlasson, R. A., Barton, C. J., Kemp, J. L., Crossley, K. M., & Davis, A. M. (2021) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2020.12.024 · Cited by 327
Hunt, M. A., Keefe, F. J., Bryant, C., Metcalf, B., Ahamed, Y., Nicholas, M. K., & Bennell, K. L. (2012) · The Knee · doi:10.1016/j.knee.2012.07.008 · Cited by 316
Self-citationBandak, E., Christensen, R., Overgaard, A., Kristensen, L. E., Ellegaard, K., Guldberg–Møller, J., Bartholdy, C. R., Hunter, D. J., Altman, R. D., Bliddal, H., et al. (2021) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2021-221129 · Cited by 313
Nissen, N., Holm, P. M., Bricca, A., Dideriksen, M., Tang, L. H., & Skou, S. T. (2021) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2021.11.008 · Cited by 303
Unraveling Negative Expectations and Nocebo-Related Effects in Musculoskeletal Pain
Rossettini, G., Colombi, A., Carlino, E., Manoni, M., Mirandola, M., Polli, A., Camerone, E. M., & Testa, M. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.789377 · Cited by 294
Three steps to changing the narrative about knee osteoarthritis care: a call to action
Cañeiro, J. P., O’Sullivan, P., Roos, E. M., Smith, A. J., Choong, P., Dowsey, M. M., Hunter, D. J., Kemp, J. L., Rodriguez, J., Lohmander, S. L., et al. (2019) · British Journal of Sports Medicine · doi:10.1136/bjsports-2019-101328 · Cited by 294
Toward a Transformed Understanding: From Pain and Movement to Pain With Movement
Butera, K. A., Fox, E. J., & George, S. Z. (2016) · Physical Therapy · doi:10.2522/ptj.20160211 · Cited by 291
Reductions in co-contraction following neuromuscular re-education in people with knee osteoarthritis
Preece, S. J., Jones, R. K., Brown, C. A., Cacciatore, T. W., & Jones, A. K. P. (2016) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-016-1209-2 · Cited by 283
Brandon, S. C. E., Miller, R. H., Thelen, D. G., & Deluzio, K. J. (2014) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2014.01.038 · Cited by 277
Postural control and thigh muscle activity in men with knee osteoarthritis
Lyytinen, T., Liikavainio, T., Bragge, T., Hakkarainen, M., Karjalainen, P. A., & Arokoski, J. P. (2010) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2010.05.005 · Cited by 276
Zhang, L., Fu, T., Zhang, Q., Yin, R., Zhu, L., He, Y. L., Fu, W., & Shen, B. (2017) · Psychology Health & Medicine · doi:10.1080/13548506.2017.1282160 · Cited by 265
Harrow, A., Wells, M., Humphris, G. M., Taylor, C., & Williams, B. (2008) · Patient Education and Counseling · doi:10.1016/j.pec.2008.07.014 · Cited by 249
A new integrated behavioural intervention for knee osteoarthritis: development and pilot study
Preece, S. J., Brookes, N., Williams, A. E., Jones, R. K., Starbuck, C., Jones, A. K. P., & Walsh, N. E. (2021) · BMC Musculoskeletal Disorders · doi:10.1186/s12891-021-04389-0 · Cited by 245
Gain of postural responses increases in response to real and anticipated pain
Hodges, P. W., Tsao, H., & Sims, K. (2015) · Experimental Brain Research · doi:10.1007/s00221-015-4347-0 · Cited by 240
Devcich, D. A., Ellis, C. J., Waltham, N., Broadbent, E., & Petrie, K. J. (2013) · British Journal of Health Psychology · doi:10.1111/bjhp.12080 · Cited by 231
I Can See Clearly Now: Using Active Visualisation to Improve Adherence to ART and PrEP
Jones, A. S. K., & Petrie, K. J. (2016) · AIDS and Behavior · doi:10.1007/s10461-016-1611-7 · Cited by 229
Kennedy, B. L., Currie, G. R., Kania‐Richmond, A., Emery, C. A., MacKean, G., & Marshall, D. A. (2022) · Musculoskeletal Care · doi:10.1002/msc.1620 · Cited by 227
King, R. D., Muggleton, S., Srinivasan, A., & Sternberg, M. J. E. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.438 · Cited by 225
Self-citationThe Computer Revolution in Philosophy.
Atkinson, M., & Sloman, A. (1980) · The Philosophical Quarterly · doi:10.2307/2219295 · Cited by 188
The computational support of scientific discovery
Langley, P. (2000) · International Journal of Human-Computer Studies · doi:10.1006/ijhc.2000.0396 · Cited by 113
Bryant, C. H., Muggleton, S., Kell, D. B., Reiser, P. G. K., King, R. D., & Oliver, S. G. (2001) · University of Salford Institutional Repository (University of Salford) · Cited by 53
Self-citationDeveloping a logical model of yeast metabolism
Reiser, P. G. K., King, R. D., Kell, D. B., Muggleton, S., Bryant, C. H., & Oliver, S. G. (2001) · Cited by 31
Self-citationDiscovery tools for science apps
Valdés‐Pérez, R. E. (1999) · Communications of the ACM · doi:10.1145/319382.319389 · Cited by 21
Abductive Inference of Genetic Networks
Zupan, B., Ivan Bratko, A., Demšar, J., Beck, J. R., Kuspa, A., & Shaulsky, G. (2001) · Lecture notes in computer science · doi:10.1007/3-540-48229-6_42 · Cited by 13
Active training of backpropagation neural networks using the learning by experimentation methodology
Lin, F., & Shaw, M. J. (1997) · Annals of Operations Research · doi:10.1023/a:1018999110972 · Cited by 13
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
Furukawa, K., Michie, D., & Muggleton, S. (1999) · Intelligent Agents · Cited by 4
Self-citation
Research works printed but not linked: 6
- Buchanan, B. G., Sutherland, G. L. & Feigenbaum, E. A. in Machine Intelligence Vol. 4 (eds Meltzer, B. & Michie, D.) 209–254 (Edinburgh Univ. Press, 1969)
- Z̈ytkow, J. M., Zhu, J. & Hussam, A. Automated discovery in a chemistry laboratory. in Proceedings of the 8th National Conference on Artificial Intelligence (AAAI-1990) (eds Dietterich, T. & Swartout, W.) 889–894 (MIT, Cambridge, Massachusetts, 1990)
- Pierce, C. S. Collected Papers of Charles Sanders Pierce (Harvard Univ. Press, 1958)
- Mitchell, T. M. Machine Learning (McGraw-Hill, New York, 1997)
- Muggleton, S. & Page, D. in Machine Intelligence Vol. 15 (eds Furukawa, K., Michie, D. & Muggleton, S.) 248–267 (Oxford Univ. Press, 1999)
- Cochran, W. G. & Cox, G. M. Experimental Designs (Wiley, New York, 1992)
Cited by
Sorted by citations
(2009) · Minds at UW (University of Wisconsin) · Cited by 4,791
Distilling Free-Form Natural Laws from Experimental Data
Schmidt, M., & Lipson, H. (2009) · Science · doi:10.1126/science.1165893 · Cited by 3,327
Probabilistic machine learning and artificial intelligence
Ghahramani, Z. (2015) · Nature · doi:10.1038/nature14541 · Cited by 1,995
Burger, B., Maffettone, P. M., Gusev, V. V., Aitchison, C. M., Bai, Y., Wang, X., Li, X., Alston, B. M., Li, B., Clowes, R., et al. (2020) · Nature · doi:10.1038/s41586-020-2442-2 · Cited by 1,516
Hutter, F., Kotthoff, L., & Vanschoren, J. (2019) · The Springer series on challenges in machine learning · doi:10.1007/978-3-030-05318-5 · Cited by 1,691
Metadata
- Authors
- King, R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S. H., Kell, D. B., & Oliver, S. G.
- Affiliations
- Aberystwyth University (GB)
- Robert Gordon University (GB)
- Imperial College London (GB)
- University of Manchester (GB)
- Corresponding author
- Oliver, Stephen G.
- Venue
- Nature
- Published
- 2004-01
- Volume
- 427
- Issue
- 6971
- Pages
- 247-252
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2136636278
- Cited by
- 662
- References
- 29
- Citations by year
- 2026: 26 · 2025: 31 · 2024: 26 · 2023: 54 · 2022: 52 · 2021: 27 · 2020: 30 · 2019: 33 · 2018: 15 · 2017: 25 · 2016: 14 · 2015: 22 · 2014: 25 · 2013: 24 · 2012: 24
- FWCI
- 106.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- University of Salford Institutional Repository (University of Salford) (submittedVersion, cc-by)
- Funders
- National Institute for Health and Care Research (NIHR202203)
- Department of Health and Social Care
- Engineering and Physical Sciences Research Council (GR/R60621/01, GR/R54071/01)
- Biotechnology and Biological Sciences Research Council (E19354)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- robot scientists, automated hypothesis generation, automated experimentation, laboratory automation, gene function analysis, deletion mutants, Saccharomyces cerevisiae, aromatic amino acid biosynthesis, metabolic pathway modeling, artificial intelligence in science
- MeSH terms
- Workforce, Algorithms, Amino Acids, Computer Simulation, Cost-Benefit Analysis, Efficiency, Genes, Fungal, Humans, Learning, Models, Biological, Phenotype, Probability, Research, Research Design, Research Personnel, Robotics, Saccharomyces cerevisiae, Software, Time Factors, Open Reading Frames, Gene Deletion, Computational Biology, Genomics, Saccharomyces cerevisiae Proteins
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
