King, Ross D.

The automation of science

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

Scientific Computing and Data ManagementBiomedical Text Mining and Ontologies

Cited by 679

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

Scientific Computing and Data ManagementBioinformatics and Genomic Networks

Cited by 662

StatLog: Comparison of classification algorithms on large real-world problems

KING, R. D., FENG, C., & SUTHERLAND, A. (1995) · Applied Artificial Intelligence

Data Mining and Machine Learning ApplicationsMachine Learning and Data Classification

Cited by 320

Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase.

King, R. D., Muggleton, S., Lewis, R. A., & Sternberg, M. J. (1992) · Proceedings of the National Academy of Sciences

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 219

Statistical evaluation of the Predictive Toxicology Challenge 2000–2001

Toivonen, H., Srinivasan, A., King, R. D., Kramer, S., & Helma, C. (2003) · Bioinformatics

Computational Drug Discovery MethodsCarcinogens and Genotoxicity Assessment

Cited by 196

An ontology for a robot scientist

Soldatova, L. N., Clare, A., Sparkes, A., & King, R. D. (2006) · Bioinformatics

Biomedical Text Mining and OntologiesSemantic Web and Ontologies

Cited by 72

Large-Scale Assessment of Deep Relational Machines

Dash, T., Srinivasan, A., Vig, L., Orhobor, O. I., & King, R. D. (2018) · Lecture Notes in Computer Science

Logic, Reasoning, and KnowledgeNeural Networks and Applications

Cited by 19

Quantitative pharmacophore models with inductive logic programming

Srinivasan, A., Page, D., Camacho, R., & King, R. (2006) · Machine Learning

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 15

Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems

Kramer, S., Cerrato, M., Brugger, J., Džeroski, S., & King, R. (2023) · arXiv

Machine Learning in Materials ScienceEvolutionary Algorithms and Applications

Cited by 10