Ross D. King
Ross Donald King
|Known for||Robot Scientist|
|Thesis||A machine learning approach to the problem of predicting a protein's secondary structure from its primary structure (PROMIS) (1989)|
Ross Donald King is a Professor of Machine Intelligence in the School of Computer Science at the University of Manchester working at the Manchester Institute of Biotechnology and Machine Learning and Optimisation (MLO) group.
King completed a Bachelor of Science degree in Microbiology at the University of Aberdeen in 1983 and went on to study for a Master of Science degree in Computer Science at the University of Newcastle in 1985. Following this, he completed a PhD at The Turing Institute at the University of Strathclyde in 1989 for work on developing machine learning methods for protein structure prediction.
King's research interests are in the automation of science, drug design, AI, machine learning and synthetic biology. He is probably best known for the Robot Scientist project which has created a robot that can:
- hypothesize to explain observations
- devise experiments to test these hypotheses
- physically run the experiments using laboratory robotics
- interpret the results from the experiments
- repeat the cycle as required
The Robot Scientist can autonomously execute high-throughput hypothesis led research. In addition to automating experimentation Robot Scientists are well suited to recording scientific knowledge: as the experiments are conceived and executed automatically by computer, it is possible to completely capture and digitally curate all aspects of the scientific process. Robot Scientist is the first machine to have been demonstrated to have discovered novel scientific knowledge. A new Robot Scientist Eve is designed to automate drug discovery. Eve automates high-throughput screening, hit confirmation, and lead generation through QSAR learning and testing. Eve is being applied to the discovery of lead compounds for neglected tropical diseases.
King's research has been funded by the EPSRC and the BBSRC., European Union, HEFCW, the Royal Academy of Engineering and JISC. He worked at Aberystwyth University for 15 years before moving to Manchester in January 2012.
In 2000 King was a founder of the spin-out company PharmaDM, which developed data mining tools for the pharmaceutical industry. The company was based largely on research applying data mining to bioinformatics and chemoinformatics. The other scientific founders come from the University of Oxford and Leuven.
King has also developed an algorithm for converting protein coding DNA sequences into music with Colin Angus of The Shamen. The song S2-translation based on this is in the Rough Guide to Rock, and was on an album that sold more than 100,000 copies.
- Sparkes, A.; Aubrey, W.; Byrne, E.; Clare, A.; Khan, M. N.; Liakata, M.; Markham, M.; Rowland, J.; Soldatova, L. N.; Whelan, K. E.; Young, M.; King, R. D. (2010). "Towards Robot Scientists for autonomous scientific discovery". Automated Experimentation. 2: 1. doi:10.1186/1759-4499-2-1. PMC 2813846. PMID 20119518.
- King, P.; Rowland, J.; Aubrey, W.; Liakata, M.; Markham, M.; Soldatova, L. N.; Whelan, K. E.; Clare, A.; Young, M.; Sparkes, A.; Oliver, S. G.; Pir, P. (2009). "The Robot Scientist Adam". Computer. 42 (7): 46–54. doi:10.1109/MC.2009.270.
- Ross D. King publications indexed by Google Scholar
- "Aberystwyth University - Robot Scientist". Archived from the original on 2013-03-05.
- "Professor escorted from university by police | Cambrian News Online 2012-04-11". Archived from the original on 2013-05-31.
- King, Ross (1989). A machine learning approach to the problem of predicting a protein's secondary structure from its primary structure (PROMIS) (PhD thesis). University of Strathclyde.
- King, Ross D.; Muggleton, Stephen H.; Srinivasan, A.; Sternberg, M. J. (1996). "Structure-activity relationships derived by machine learning: The use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming". Proceedings of the National Academy of Sciences of the United States of America. 93 (1): 438–442. doi:10.1073/pnas.93.1.438. PMC 40253. PMID 8552655.
- "Professor Ross King, University of Manchester". Archived from the original on 2013-03-05.
- "Machine Learning and Optimization (MLO) School of Computer Science".
- Ross D. King at DBLP Bibliography Server
- "Professor Ross King (Manchester Institute of Biotechnology – The University of Manchester)". Archived from the original on 2013-03-05.
- Ross D. King's publications indexed by the Scopus bibliographic database. (subscription required)
- Ross D. King author profile page at the ACM Digital Library
- Srinivasan, A.; Muggleton, S.H.; Sternberg, M.J.E.; King, R.D. (1996). "Theories for mutagenicity: A study in first-order and feature-based induction". Artificial Intelligence. 85 (1–2): 277–299. doi:10.1016/0004-3702(95)00122-0.
- King, R. D.; Sternberg, M. J. E. (1990). "Machine learning approach for the prediction of protein secondary structure". Journal of Molecular Biology. 216 (2): 441–457. doi:10.1016/S0022-2836(05)80333-X. PMID 2254939.
- King, R. D.; Sternberg, M. J. E. (1996). "Identification and application of the concepts important for accurate and reliable protein secondary structure prediction". Protein Science. 5 (11): 2298–2310. doi:10.1002/pro.5560051116. PMC 2143286. PMID 8931148.
- King, R. D.; Muggleton, S.; Lewis, R. A.; Sternberg, M. J. (1992). "Drug design by machine learning: The use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase". Proceedings of the National Academy of Sciences of the United States of America. 89 (23): 11322–11326. doi:10.1073/pnas.89.23.11322. PMC 50542. PMID 1454814.
- King, R. D.; Liakata, M.; Lu, C.; Oliver, S. G.; Soldatova, L. N. (2011). "On the formalization and reuse of scientific research". Journal of the Royal Society Interface. 8 (63): 1440–1448. doi:10.1098/rsif.2011.0029. PMC 3163424. PMID 21490004.
- Anderson, Philip W.; Abrahams, Elihu (2009). "Machines Fall Short of Revolutionary Science". Science. 324 (5934): 1515–1516. Bibcode:2009Sci...324.1515A. doi:10.1126/science.324_1515c. PMID 19541975.
- Waltz, David; Buchanan, Bruce G. (2009). "Automating Science: Computers with intelligence can design and run experiments, but learning from the results to generate subsequent experiments requires even more intelligence". Science. 324 (5923): 43–44. doi:10.1126/science.1172781. PMID 19342574.
- Stevenson, R. W.; Murphy, J. F.; Clare, T. J. (2009). "Robot Inventors: Patently Impossible?". Science. 324 (5930): 1014. doi:10.1126/science.324_1014a. PMID 19460985.
- King, R. D.; Rowland, J.; Oliver, S. G.; Young, M.; Aubrey, W.; Byrne, E.; Liakata, M.; Markham, M.; Pir, P.; Soldatova, L. N.; Sparkes, A.; Whelan, K. E.; Clare, A. (2009). "Make Way for Robot Scientists". Science. 325 (5943): 945. Bibcode:2009Sci...325R.945K. doi:10.1126/science.325_945a. PMID 19696334.
- King, R. D.; Rowland, J.; Oliver, S. G.; Young, M.; Aubrey, W.; Byrne, E.; Liakata, M.; Markham, M.; Pir, P.; Soldatova, L. N.; Sparkes, A.; Whelan, K. E.; Clare, A. (2009). "The Automation of Science". Science. 324 (5923): 85–89. Bibcode:2009Sci...324...85K. doi:10.1126/science.1165620. PMID 19342587.
- 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. (2004). "Functional genomic hypothesis generation and experimentation by a robot scientist". Nature. 427 (6971): 247–252. doi:10.1038/nature02236. PMID 14724639.
- King, R. D. (2011). "Rise of the Robo Scientists". Scientific American. 304: 72–76. doi:10.1038/scientificamerican0111-72.
- "2 April 2009 - Robot scientist becomes first machine to discover new scientific knowledge - Media release - BBSRC". Archived from the original on 2013-02-24.
- Wilson, N. (2004). "Technology: A robot scientist". Nature Reviews Genetics. 5 (3): 164. doi:10.1038/nrg1300.
- "Grants awarded to Ross King by the Engineering and Physical Sciences Research Council (EPSRC)".
- "Music to my DNA structure". Times Higher Education 2001-05-25.
- on YouTube
- Buckley, Peter J. (2003). The Rough Guide to Rock (Rough Guides). Rough Guides Limited. ISBN 978-1-84353-105-0.
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