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An ontology for a Robot Scientist
Open accessAbstract
Motivation: A Robot Scientist is a physically implemented robotic system that can automatically carry out cycles of scientific experimentation. We are commissioning a new Robot Scientist designed to investigate gene function in S. cerevisiae. This Robot Scientist will be capable of initiating >1,000 experiments, and making >200,000 observations a day. Robot Scientists provide a unique test bed for the development of methodologies for the curation and annotation of scientific experiments: because the experiments are conceived and executed automatically by computer, it is possible to completely capture and digitally curate all aspects of the scientific process. This new ability brings with it significant technical challenges. To meet these we apply an ontology driven approach to the representation of all the Robot Scientist’s data and metadata. Results: We demonstrate the utility of developing an ontology for our new Robot Scientist. This ontology is based on a general ontology of experiments. The ontology aids the curation and annotating of the experimental data and metadata, and the equipment metadata, and supports the design of database systems to hold the data and metadata. Availability: EXPO in XML and OWL formats is at: . All materials about the Robot Scientist project are available at: . Contact: lss@aber.ac.uk
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The robot scientist developed by King et al. and its applications in functional genomics illustrate how a machine can discover novel scientific knowledge in a fully automatic manner.
“A prominent example is the robot scientist developed by King et al. [224–226] and its applications in functional genomics, illustrating how a machine can discover novel scientific knowledge in a fully automatic manner.”
From Reverse engineering and identification in systems biology: strategies, perspectives and challenges (2014) · cites this paper as [225]
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Minimum information about a microarray experiment (MIAME)-toward standards for microarray data
Brazma, A., Hingamp, P., Quackenbush, J., Sherlock, G., Spellman, P., Stoeckert, C., Aach, J., Ansorge, W., Ball, C. A., Causton, H. C., et al. (2001) · Nature Genetics · doi:10.1038/ng1201-365 · Cited by 4,109
Functional genomic hypothesis generation and experimentation by a robot scientist
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) · Nature · doi:10.1038/nature02236 · Cited by 662
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Part 1: Introduction to ontological engineering
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Are the current ontologies in biology good ontologies?
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ten Teije, A., Hernandez, N., Aussenac-Gilles, N., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33876-2 · Cited by 42
Building a cell and anatomy ontology of Caenorhabditis elegans
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Enzymatic and Physiological Properties of the Yeast Glutamate-α-Ketoadipate Transaminase
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King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., Liakata, M., Markham, M., Pir, P., Soldatova, L. N., et al. (2009) · Science · doi:10.1126/science.1165620 · Cited by 679
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Morgan, D., & Jacobs, R. (2020) · Annual Review of Materials Research · doi:10.1146/annurev-matsci-070218-010015 · Cited by 549
Reverse engineering and identification in systems biology: strategies, perspectives and challenges
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Metadata
- Authors
- Soldatova, L. N., Clare, A., Sparkes, A., & King, R. D.
- Affiliations
- Aberystwyth University (GB)
- Corresponding author
- Soldatova, Larisa N.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-07-15
- Volume
- 22
- Issue
- 14
- Pages
- e464-e471
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2128396257
- Cited by
- 72
- References
- 17
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 2 · 2020: 5 · 2019: 3 · 2018: 1 · 2017: 6 · 2016: 3 · 2015: 6 · 2014: 1 · 2013: 5 · 2012: 4
- FWCI
- 2.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion)
- Funders
- Biotechnology and Biological Sciences Research Council
- Topics
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- robot scientists, ontology (information science), metadata annotation, database design, Saccharomyces cerevisiae, gene function
- MeSH terms
- Artificial Intelligence, Database Management Systems, Documentation, Natural Language Processing, Research, Research Design, Robotics, Saccharomyces cerevisiae, Science, Databases, Factual, Information Storage and Retrieval, Vocabulary, Controlled, Cell Culture Techniques, Saccharomyces cerevisiae Proteins
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