Ross D. King

136 papers A* 4A 3B 18C 10Misc 2Journal 76Unranked 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
The future of fundamental science led by generative closed-loop artificial intelligence.
Frontiers Artif. Intell.
Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Jonathan E. Rowe, James A. Evans, Hiroaki Kitano, Ross D. King
2025 J jnl
Compressing Chemistry Reveals Functional Groups.
CoRR
Ruben Sharma, Ross D. King
2025 J jnl
Improved Machine Learning Predictions of EC50s Using Uncertainty Estimation from Dose-Response Data.
J. Chem. Inf. Model.
Hugo Bellamy, Joachim Dickhaut, Ross D. King
2025 — conf
LLM-retrieval based scientific knowledge grounding.
ESWC-JP
Gabriel K. Reder, Carl Collins, Abbi Abdel Rehim, Larisa N. Soldatova, Ross D. King
2025 J jnl
Learning Logical Rules using Minimum Message Length.
CoRR
Ruben Sharma, Sebastijan Dumancic, Ross D. King, Andrew Cropper
2025 J jnl
Mitigating Hallucinations in Zero-Shot Scientific Summarisation: A Pilot Study.
CoRR
Imane Jaaouine, Ross D. King
2025 C conf
Ontology-based box embeddings and knowledge graphs for predicting phenotypic traits in Saccharomyces cerevisiae.
NeSy
Filip Kronström, Daniel Brunnsåker, Ievgeniia A. Tiukova, Ross D. King
2024 J jnl
Automating the Practice of Science - Opportunities, Challenges, and Implications.
CoRR
Sebastian Musslick, Laura Bartlett, Suyog H. Chandramouli, Marina Dubova, Fernand Gobet, Thomas L. Griffiths, Jessica Hullman, Ross D. King, J. Nathan Kutz, Christopher G. Lucas, Suhas Mahesh, Franco Pestilli, Sabina J. Sloman, William R. Holmes
2024 J jnl
Extrapolation is not the same as interpolation.
Mach. Learn.
Yuxuan Wang, Ross D. King
2024 J jnl
Genesis: Towards the Automation of Systems Biology Research.
CoRR
Ievgeniia A. Tiukova, Daniel Brunnsåker, Erik Y. Bjurström, Alexander H. Gower, Filip Kronström, Gabriel K. Reder, Ronald S. Reiserer, Konstantin Korovin, Larisa N. Soldatova, John P. Wikswo, Ross D. King
2024 J jnl
Interpreting protein abundance in
Bioinform.
Daniel Brunnsåker, Filip Kronström, Ievgeniia A. Tiukova, Ross D. King
2024 J jnl
Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture.
CoRR
Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Gareth Griffiths, Larisa N. Soldatova, Ross D. King
2024 — conf
Random Forests for Heteroscedastic Data.
DS (2)
Hugo Bellamy, Ross D. King
2024 J jnl
Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment.
CoRR
Abbi Abdel-Rehim, Hector Zenil, Oghenejokpeme I. Orhobor, Marie Fisher, Ross J. Collins, Elizabeth Bourne, Gareth W. Fearnley, Emma Tate, Holly X. Smith, Larisa N. Soldatova, Ross D. King
2024 J jnl
The Use of AI-Robotic Systems for Scientific Discovery.
CoRR
Alexander H. Gower, Konstantin Korovin, Daniel Brunnsåker, Filip Kronström, Gabriel K. Reder, Ievgeniia A. Tiukova, Ronald S. Reiserer, John P. Wikswo, Ross D. King
2023 J jnl
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems.
CoRR
Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King
2023 J jnl
Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction.
CoRR
Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Hang Lou, Hao Ni, Ross D. King
2023 J jnl
Extension of Transformational Machine Learning: Classification Problems.
CoRR
Adnan Mahmud, Oghenejokpeme I. Orhobor, Ross D. King
2023 B conf
Extrapolation is Not the Same as Interpolation.
DS
Yuxuan Wang, Ross D. King
2023 J jnl
Imbalanced regression using regressor-classifier ensembles.
Mach. Learn.
Oghenejokpeme I. Orhobor, Nastasiya F. Grinberg, Larisa N. Soldatova, Ross D. King
2023 B conf
LGEM
DS
Alexander H. Gower, Konstantin Korovin, Daniel Brunnsåker, Ievgeniia A. Tiukova, Ross D. King
2023 J jnl
Protein-ligand binding affinity prediction exploiting sequence constituent homology.
Bioinform.
Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Hang Lou, Hao Ni, Ross D. King
2023 B conf
RIMBO - An Ontology for Model Revision Databases.
DS
Filip Kronström, Alexander H. Gower, Ievgeniia A. Tiukova, Ross D. King
2023 J jnl
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence.
CoRR
Hector Zenil, Jesper Tegnér, Felipe S. Abrahão, Alexander Lavin, Vipin Kumar, Jeremy G. Frey, Adrian Weller, Larisa N. Soldatova, Alan R. Bundy, Nicholas R. Jennings, Koichi Takahashi, Lawrence Hunter, Saso Dzeroski, Andrew Briggs, Frederick D. Gregory, Carla P. Gomes, Christopher K. I. Williams, Jonathan E. Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King
2022 J jnl
Batched Bayesian Optimization for Drug Design in Noisy Environments.
J. Chem. Inf. Model.
Hugo Bellamy, Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Ross D. King
2022 J jnl
Improved prediction of gene expression through integrating cell signalling models with machine learning.
BMC Bioinform.
Nada Al taweraqi, Ross D. King
2021 J jnl
Cross-validation is safe to use.
Nat. Mach. Intell.
Ross D. King, Oghenejokpeme I. Orhobor, Charles C. Taylor
2020 J jnl
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat.
Mach. Learn.
Nastasiya F. Grinberg, Oghenejokpeme I. Orhobor, Ross D. King
2020 B conf
Federated Ensemble Regression Using Classification.
DS
Oghenejokpeme I. Orhobor, Larisa N. Soldatova, Ross D. King
2020 B conf
Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology.
DS
Oghenejokpeme I. Orhobor, Joseph French, Larisa N. Soldatova, Ross D. King
2020 J jnl
Predicting rice phenotypes with meta and multi-target learning.
Mach. Learn.
Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King
2020 — conf
Self-supervised learning of object slippage: An LSTM model trained on low-cost tactile sensors.
IRC
Ainur Begalinova, Ross D. King, Barry Lennox, Riza Batista-Navarro
2019 J jnl
Multi-task learning with a natural metric for quantitative structure activity relationship learning.
J. Cheminformatics
Noureddin Sadawi, Iván Olier, Joaquin Vanschoren, Jan N. van Rijn, Jeremy Besnard, G. Richard J. Bickerton, Crina Grosan, Larisa N. Soldatova, Ross D. King
2019 — conf
Using Prior Knowledge to Facilitate Computational Reading of Arabic Calligraphy.
IDEAL (2)
Seetah ALSalamah, Riza Batista-Navarro, Ross D. King
2018 J jnl
Automating Sciences: Philosophical and Social Dimensions.
IEEE Technol. Soc. Mag.
Ross D. King, Vlad Schuler Costa, Chris Mellingwood, Larisa N. Soldatova
2018 B conf
Large-Scale Assessment of Deep Relational Machines.
ILP
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King
2018 J jnl
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery.
Mach. Learn.
Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King
2018 B conf
Predicting Rice Phenotypes with Meta-learning.
DS
Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King
2018 — conf
Towards the Machine Reading of Arabic Calligraphy: A Letters Dataset and Corresponding Corpus of Text.
ASAR
Seetah ALSalamah, Ross D. King
2018 J jnl
Transformative Machine Learning.
CoRR
Iván Olier, Oghenejokpeme I. Orhobor, Joaquin Vanschoren, Ross D. King
2017 J jnl
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery.
CoRR
Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King
2016 J jnl
Computing exponentially faster: Implementing a nondeterministic universal Turing machine using DNA.
CoRR
Andrew Currin, Konstantin Korovin, Maria Ababi, Katherine Roper, Douglas B. Kell, Philip J. Day, Ross D. King
2016 J jnl
On the Use of Computer Programs as Money.
CoRR
Ross D. King
2015 — conf
Automating the Development of Metabolic Network Models.
CMSB
Robert Rozanski, Stefano Bragaglia, Oliver Ray, Ross D. King
2015 — conf
Meta-QSAR: Learning How to Learn QSARs.
MetaSel@PKDD/ECML
Iván Olier, Crina Grosan, Noureddin Sadawi, Larisa N. Soldatova, Ross D. King
2014 J jnl
An investigation into eukaryotic pseudouridine synthases.
J. Bioinform. Comput. Biol.
Ross D. King, Chuan Lu
2014 J jnl
EXACT2: the semantics of biomedical protocols.
BMC Bioinform.
Larisa N. Soldatova, Daniel Nadis, Ross D. King, Piyali S. Basu, Emma Haddi, Véronique Baumlé, Nigel J. Saunders, Wolfgang Marwan, Brian B. Rudkin
2014 A* conf
Predicting the Geographical Origin of Music.
ICDM
Fang Zhou, Claire Q, Ross D. King
2013 J jnl
Representation of probabilistic scientific knowledge.
J. Biomed. Semant.
Larisa N. Soldatova, Andrey Rzhetsky, Kurt De Grave, Ross D. King
2012 B conf
Topic Models with Relational Features for Drug Design.
ILP
Tanveer A. Faruquie, Ashwin Srinivasan, Ross D. King
2011 J jnl
Numbers as Data Structures: The Prime Successor Function as Primitive
CoRR
Ross D. King
2011 J jnl
Qualitative System Identification from Imperfect Data
CoRR
George Macleod Coghill, Ross D. King, Ashwin Srinivasan
2010 J jnl
An Ontology for Description of Drug Discovery Investigations.
J. Integr. Bioinform.
Da Qi, Ross D. King, Andrew L. Hopkins, G. Richard J. Bickerton, Larisa N. Soldatova
2010 J jnl
Further developments towards a genome-scale metabolic model of yeast.
BMC Syst. Biol.
Paul D. Dobson, Kieran Smallbone, Daniel Jameson, Evangelos Simeonidis, Karin Lanthaler, Pinar Pir, Chuan Lu, Neil Swainston, Warwick B. Dunn, Paul Fisher, Duncan Hull, Marie Brown, Olusegun Oshota, Natalie J. Stanford, Douglas B. Kell, Ross D. King, Stephen G. Oliver, Robert D. Stevens, Pedro Mendes
2010 — ch.
Inductive Queries for a Drug Designing Robot Scientist.
Inductive Databases and Constraint-Based Data Mining
Ross D. King, Amanda C. Schierz, Amanda Clare, Jem J. Rowland, Andrew Sparkes, Siegfried Nijssen, Jan Ramon
2010 Misc conf
Logic-Based Steady-State Analysis and Revision of Metabolic Networks with Inhibition.
CISIS
Oliver Ray, Ken E. Whelan, Ross D. King
2010 C conf
The Analysis of Yeast Cell Morphology Using a Robot Scientist.
CIS
Yihui Liu, Katherine Martin, Andrew Sparkes, Ross D. King
2009 Misc conf
A Nonmonotonic Logical Approach for Modelling and Revising Metabolic Networks.
CISIS
Oliver Ray, Ken E. Whelan, Ross D. King
2009 J jnl
An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems.
Bioinform.
Chuan Lu, Ross D. King
2009 B conf
Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data.
ILP
Oliver Ray, Ken E. Whelan, Ross D. King
2009 — conf
Drugs and Drug-Like Compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds.
PRIB
Amanda C. Schierz, Ross D. King
2009 J jnl
The Robot Scientist Adam.
Computer
Ross D. King, Jem J. Rowland, Wayne Aubrey, Maria Liakata, Magdalena Markham, Larisa N. Soldatova, Ken E. Whelan, Amanda Clare, Mike Young, Andrew Sparkes, Stephen G. Oliver, Pinar Pir
2008 — conf
Formalising Phylogenetic Experiments: Ontologies and Logical Inference.
AAAI Spring Symposium: Symbiotic Relationships between Semantic Web and Knowledge Engineering
Ross D. King, Larisa N. Soldatova
2008 J jnl
Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming.
J. Mach. Learn. Res.
Ashwin Srinivasan, Ross D. King
2008 J jnl
Qualitative System Identification from Imperfect Data.
J. Artif. Intell. Res.
George Macleod Coghill, Ashwin Srinivasan, Ross D. King
2008 A conf
The EXACT description of biomedical protocols.
ISMB
Larisa N. Soldatova, Wayne Aubrey, Ross D. King, Amanda Clare
2008 J jnl
Using a logical model to predict the growth of yeast.
BMC Bioinform.
Ken E. Whelan, Ross D. King
2007 C conf
Active Learning for Regression Based on Query by Committee.
IDEAL
Robert Burbidge, Jem J. Rowland, Ross D. King
2007 C conf
Evolutionary Optimization of Three-Photon Absorption in Molecular Iodine.
CIDM
Robert Burbidge, Jem J. Rowland, Ross D. King, Nicholas T. Form, Benjamin J. Whitaker
2007 — ch.
Learning Qualitative Models of Physical and Biological Systems.
Computational Discovery of Scientific Knowledge
Simon M. Garrett, George Macleod Coghill, Ashwin Srinivasan, Ross D. King
2007 J jnl
Locational distribution of gene functional classes in
BMC Bioinform.
Michael C. Riley, Amanda Clare, Ross D. King
2007 — ch.
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics.
Computational Discovery of Scientific Knowledge
Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe
2006 — conf
An ontology for a Robot Scientist.
ISMB (Supplement of Bioinformatics)
Larisa N. Soldatova, Amanda Clare, Andrew Sparkes, Ross D. King
2006 J jnl
Finding Motifs in Protein Secondary Structure for Use in Function Prediction.
J. Comput. Biol.
Sébastien Ferré, Ross D. King
2006 J jnl
Functional bioinformatics for
Bioinform.
Amanda Clare, Andreas Karwath, Helen Ougham, Ross D. King
2006 J jnl
Functional bioinformatics for
Bioinform.
Amanda Clare, Andreas Karwath, Helen Ougham, Ross D. King
2006 J jnl
Guest editorial.
Mach. Learn.
Rui Camacho, Ross D. King, Ashwin Srinivasan
2006 J jnl
Quantitative pharmacophore models with inductive logic programming.
Mach. Learn.
Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King
2006 J jnl
Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships.
J. Comput. Aided Mol. Des.
Bård Buttingsrud, Einar Ryeng, Ross D. King, Bjørn K. Alsberg
2005 J jnl
A Dichotomic Search Algorithm for Mining and Learning in Domain-Specific Logics.
Fundam. Informaticae
Sébastien Ferré, Ross D. King
2005 J jnl
On the use of qualitative reasoning to simulate and identify metabolic pathway.
Bioinform.
Ross D. King, Simon M. Garrett, George Macleod Coghill
2005 B conf
The Robot Scientist Project.
ALT
Ross D. King
2005 B conf
The Robot Scientist Project.
Discovery Science
Ross D. King, Michael Young, Amanda Clare, Kenneth Whelan, Jem J. Rowland
2004 J jnl
Applying Inductive Logic Programming to Predicting Gene Function.
AI Mag.
Ross D. King
2004 C conf
BLID: An Application of Logical Information Systems to Bioinformatics.
ICFCA
Sébastien Ferré, Ross D. King
2004 J jnl
Confirmation of data mining based predictions of protein function.
Bioinform.
Ross D. King, Paul H. Wise, Amanda Clare
2004 B ed.
Inductive Logic Programming, 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings
ILP
Rui Camacho, Ross D. King, Ashwin Srinivasan
2004 A conf
Learning Qualitative Metabolic Models.
ECAI
George Macleod Coghill, Simon M. Garrett, Ross D. King
2004 C conf
Poly-transformation.
IDEAL
Ross D. King, Mohammed Ouali
2003 B conf
A Personal View of How Best to Apply ILP.
ILP
Ross D. King
2003 J jnl
An Empirical Study of the Use of Relevance Information in Inductive Logic Programming.
J. Mach. Learn. Res.
Ashwin Srinivasan, Ross D. King, Michael Bain
2003 — conf
Application of Inductive Logic Programming to Structure-Based Drug Design.
PKDD
David P. Enot, Ross D. King
2003 C conf
Data Mining the Yeast Genome in a Lazy Functional Language.
PADL
Amanda Clare, Ross D. King
2003 C conf
Predicting gene function in Saccharomyces cerevisiae.
ECCB
Amanda Clare, Ross D. King
2003 J jnl
Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001.
Bioinform.
Hannu Toivonen, Ashwin Srinivasan, Ross D. King, Stefan Kramer, Christoph Helma
2002 C conf
Application of metabolomics to plant genotype discrimination using statistics and machine learning.
ECCB
Janet Taylor, Ross D. King, Thomas Altmann, Oliver Fiehn
2002 J jnl
Homology Induction: the use of machine learning to improve sequence similarity searches.
BMC Bioinform.
Andreas Karwath, Ross D. King
2002 J jnl
How well do we understand the clusters found in microarray data?
Silico Biol.
Amanda Clare, Ross D. King
2002 J jnl
Machine learning of functional class from phenotype data.
Bioinform.
Amanda Clare, Ross D. King
2001 J jnl
A quantum mechanics based representation of molecules for machine inference.
Electron. Trans. Artif. Intell.
Ross D. King, Nathalie Marchand-Geneste, Bjørn K. Alsberg
2001 B conf
An Automated ILP Server in the Field of Bioinformatics.
ILP
Andreas Karwath, Ross D. King
2001 J jnl
Combining Inductive Logic Programming, Active Learning and Robotics to Discover the Function of Genes.
Electron. Trans. Artif. Intell.
Christopher H. Bryant, Stephen H. Muggleton, Stephen G. Oliver, Douglas B. Kell, Philip G. K. Reiser, Ross D. King
2001 J jnl
Developing a Logical Model of Yeast Metabolism.
Electron. Trans. Artif. Intell.
Philip G. K. Reiser, Ross D. King, Douglas B. Kell, Stephen H. Muggleton, Christopher H. Bryant, Stephen G. Oliver
2001 — conf
Knowledge Discovery in Multi-label Phenotype Data.
PKDD
Amanda Clare, Ross D. King
2001 J jnl
The Predictive Toxicology Challenge 2000-2001.
Bioinform.
Christoph Helma, Ross D. King, Stefan Kramer, Ashwin Srinivasan
2001 J jnl
The utility of different representations of protein sequence for predicting functional class.
Bioinform.
Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe
2001 J jnl
Warmr: a data mining tool for chemical data.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan, Luc Dehaspe
2000 A* conf
Genome scale prediction of protein functional class from sequence using data mining.
KDD
Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe
1999 B conf
An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment.
ILP
Ashwin Srinivasan, Ross D. King, Douglas W. Bristol
1999 A* conf
An assessment of submissions made to the Predictive Toxicology Evaluation Challenge.
IJCAI
Ashwin Srinivasan, Ross D. King, Douglas W. Bristol
1999 J jnl
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes.
Data Min. Knowl. Discov.
Ashwin Srinivasan, Ross D. King
1998 B conf
Biochemical Knowledge Discovery Using Inductive Logic Programming.
Discovery Science
Stephen H. Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg
1998 A* conf
Finding Frequent Substructures in Chemical Compounds.
KDD
Luc Dehaspe, Hannu Toivonen, Ross D. King
1998 J jnl
The discovery of indicator variables for QSAR using inductive logic programming.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan
1997 B conf
Carcinogenesis Predictions Using ILP.
ILP
Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg
1997 J jnl
DSC: public domain protein secondary structure predication.
Comput. Appl. Biosci.
Ross D. King, Mansoor A. S. Saqi, Roger A. Sayle, Michael J. E. Sternberg
1997 — conf
The Predictive Toxicology Evaluation Challenge.
IJCAI (1)
Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg
1997 J jnl
The discovery of indicator variables for QSAR using inductive logic programming.
J. Comput. Aided Mol. Des.
Ross D. King, Ashwin Srinivasan
1996 B conf
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity by Structural Attributes.
Inductive Logic Programming Workshop
Ashwin Srinivasan, Ross D. King
1996 J jnl
PM - protein music.
Comput. Appl. Biosci.
Ross D. King, C. G. Angus
1996 J jnl
Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction.
Artif. Intell.
Ashwin Srinivasan, Stephen H. Muggleton, Michael J. E. Sternberg, Ross D. King
1995 J jnl
Comparison of artificial intelligence methods for modeling pharmaceutical QSARS.
Appl. Artif. Intell.
Ross D. King
1995 — conf
Drug Design by Machine Learning.
Machine Intelligence 15
Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen H. Muggleton
1995 J jnl
Relating Chemical Activity to Structure: An Examination of ILP Successes.
New Gener. Comput.
Ross D. King, Michael J. E. Sternberg, Ashwin Srinivasan
1995 J jnl
STALOG: Comparison of classification algorithms on large real-world problems.
Appl. Artif. Intell.
Ross D. King, Cao Feng, A. Sutherland
1994 J jnl
Applications of Inductive Logic Programming.
SIGART Bull.
Ivan Bratko, Ross D. King
1994 A conf
Inductive Logic Programming Used to Discover Topological Constraints in Protein Structures.
ISMB
Ross D. King, Dominic A. Clark, Jack Shirazi, Michael J. E. Sternberg
1994 J jnl
Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines.
J. Comput. Aided Mol. Des.
Jonathan D. Hirst, Ross D. King, Michael J. E. Sternberg
1994 J jnl
Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines.
J. Comput. Aided Mol. Des.
Jonathan D. Hirst, Ross D. King, Michael J. E. Sternberg
1993 — conf
Discovery of Protein Structural Constraints in a Deductive Database using Inductive Logic Programming.
Machine Intelligence 14
Ross D. King, Dominic A. Clark, Jack Shirazi, Michael J. E. Sternberg
1992 — conf
A Comparative Study of Classification Algorithms: Statistical, Machine Learning and Neural Network.
Machine Intelligence 13
Ross D. King, Bob Henery, Cao Feng, A. Sutherland
1992 — conf
Machine Learning and biomolecular modelling.
Machine Intelligence 13
Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen H. Muggleton
1992 C conf
Statistical Methods in Learning.
IPMU
A. Sutherland, Bob Henery, Rafael Molina, Charles C. Taylor, Ross D. King
1991 — conf
IPSA: Inductive Protein Structure Analysis.
EWSL
Steffen Schulze-Kremer, Ross D. King
1988 — —
A machine learning approach to the problem of predicting a protein's secondary structure from its primary structure
Ross D. King
1987 — conf
An Inductive Learning Approach to the Problem of Predicting a Protein's Secondary Structure from Its Amino Acid Sequence.
EWSL
Ross D. King