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ORCIDRoss D. King
Person information
- affiliation: University of Cambridge, Department of Chemical Engineering and Biotechnology, UK
- affiliation: Chalmers University of Technology, Gothenburg, Sweden
- affiliation (former): Aberystwyth University, UK
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2020 – today
- 2024
[i14]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:
Scientific Hypothesis Generation by a Large Language Model: Laboratory Validation in Breast Cancer Treatment. CoRR abs/2405.12258 (2024)- [i13]Alexander H. Gower, Konstantin Korovin, Daniel Brunnsåker, Filip Kronström, Gabriel K. Reder, Ievgeniia A. Tiukova, Ronald S. Reiserer, John P. Wikswo, Ross D. King:
The Use of AI-Robotic Systems for Scientific Discovery. CoRR abs/2406.17835 (2024) - [i12]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:
Genesis: Towards the Automation of Systems Biology Research. CoRR abs/2408.10689 (2024) - [i11]Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Gareth Griffiths, Larisa N. Soldatova, Ross D. King:
Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture. CoRR abs/2408.13012 (2024) - 2023
- [j55]Abbi Abdel-Rehim
, Oghenejokpeme I. Orhobor, Hang Lou, Hao Ni, Ross D. King:
Protein-ligand binding affinity prediction exploiting sequence constituent homology. Bioinform. 39(8) (2023) - [j54]Oghenejokpeme I. Orhobor, Nastasiya F. Grinberg, Larisa N. Soldatova, Ross D. King:
Imbalanced regression using regressor-classifier ensembles. Mach. Learn. 112(4): 1365-1387 (2023) - [c52]Yuxuan Wang, Ross D. King:
Extrapolation is Not the Same as Interpolation. DS 2023: 277-292 - [c51]Filip Kronström, Alexander H. Gower, Ievgeniia A. Tiukova, Ross D. King:
RIMBO - An Ontology for Model Revision Databases. DS 2023: 523-534 - [c50]Alexander H. Gower, Konstantin Korovin, Daniel Brunnsåker, Ievgeniia A. Tiukova, Ross D. King:
LGEM+: A First-Order Logic Framework for Automated Improvement of Metabolic Network Models Through Abduction. DS 2023: 628-643 - [i10]Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Hang Lou, Hao Ni, Ross D. King:
Beating the Best: Improving on AlphaFold2 at Protein Structure Prediction. CoRR abs/2301.07568 (2023) - [i9]Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King:
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR abs/2305.02251 (2023) - [i8]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, Jon Rowe, James A. Evans, Hiroaki Kitano, Joshua B. Tenenbaum, Ross D. King:
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence. CoRR abs/2307.07522 (2023) - [i7]Adnan Mahmud, Oghenejokpeme I. Orhobor, Ross D. King:
Extension of Transformational Machine Learning: Classification Problems. CoRR abs/2309.16693 (2023) - 2022
- [j53]Nada Al taweraqi, Ross D. King:
Improved prediction of gene expression through integrating cell signalling models with machine learning. BMC Bioinform. 23(1): 323 (2022) - [j52]Hugo Bellamy, Abbi Abdel-Rehim, Oghenejokpeme I. Orhobor, Ross D. King:
Batched Bayesian Optimization for Drug Design in Noisy Environments. J. Chem. Inf. Model. 62(17): 3970-3981 (2022) - 2021
- [j51]Ross D. King, Oghenejokpeme I. Orhobor, Charles C. Taylor:
Cross-validation is safe to use. Nat. Mach. Intell. 3(4): 276 (2021) - 2020
- [j50]Nastasiya F. Grinberg, Oghenejokpeme I. Orhobor, Ross D. King:
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat. Mach. Learn. 109(2): 251-277 (2020) - [j49]Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King:
Predicting rice phenotypes with meta and multi-target learning. Mach. Learn. 109(11): 2195-2212 (2020) - [c49]Oghenejokpeme I. Orhobor, Larisa N. Soldatova, Ross D. King:
Federated Ensemble Regression Using Classification. DS 2020: 325-339 - [c48]Oghenejokpeme I. Orhobor, Joseph French, Larisa N. Soldatova, Ross D. King:
Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology. DS 2020: 374-385 - [c47]Ainur Begalinova, Ross D. King, Barry Lennox, Riza Batista-Navarro:
Self-supervised learning of object slippage: An LSTM model trained on low-cost tactile sensors. IRC 2020: 191-196
2010 – 2019
- 2019
- [j48]Noureddin Sadawi, Iván Olier, Joaquin Vanschoren, Jan N. van Rijn, Jeremy Besnard, G. Richard J. Bickerton, Crina Grosan, Larisa N. Soldatova, Ross D. King:
Multi-task learning with a natural metric for quantitative structure activity relationship learning. J. Cheminformatics 11(1): 68:1-68:13 (2019) - [c46]Seetah ALSalamah, Riza Batista-Navarro, Ross D. King:
Using Prior Knowledge to Facilitate Computational Reading of Arabic Calligraphy. IDEAL (2) 2019: 293-304 - 2018
- [j47]Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King:
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery. Mach. Learn. 107(1): 285-311 (2018) - [j46]Ross D. King, Vlad Schuler Costa, Chris Mellingwood, Larisa N. Soldatova:
Automating Sciences: Philosophical and Social Dimensions. IEEE Technol. Soc. Mag. 37(1): 40-46 (2018) - [c45]Seetah ALSalamah, Ross D. King:
Towards the Machine Reading of Arabic Calligraphy: A Letters Dataset and Corresponding Corpus of Text. ASAR 2018: 19-23 - [c44]Oghenejokpeme I. Orhobor, Nickolai N. Alexandrov, Ross D. King:
Predicting Rice Phenotypes with Meta-learning. DS 2018: 144-158 - [c43]Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Oghenejokpeme I. Orhobor, Ross D. King:
Large-Scale Assessment of Deep Relational Machines. ILP 2018: 22-37 - [i6]Iván Olier, Oghenejokpeme I. Orhobor, Joaquin Vanschoren, Ross D. King:
Transformative Machine Learning. CoRR abs/1811.03392 (2018) - 2017
- [i5]Iván Olier, Noureddin Sadawi, G. Richard J. Bickerton, Joaquin Vanschoren, Crina Grosan, Larisa N. Soldatova, Ross D. King:
Meta-QSAR: a large-scale application of meta-learning to drug design and discovery. CoRR abs/1709.03854 (2017) - 2016
- [i4]Andrew Currin, Konstantin Korovin, Maria Ababi, Katherine Roper, Douglas B. Kell, Philip J. Day, Ross D. King:
Computing exponentially faster: Implementing a nondeterministic universal Turing machine using DNA. CoRR abs/1607.08078 (2016) - [i3]Ross D. King:
On the Use of Computer Programs as Money. CoRR abs/1608.00878 (2016) - 2015
- [c42]Robert Rozanski, Stefano Bragaglia, Oliver Ray, Ross D. King:
Automating the Development of Metabolic Network Models. CMSB 2015: 145-156 - [c41]Iván Olier, Crina Grosan, Noureddin Sadawi, Larisa N. Soldatova, Ross D. King:
Meta-QSAR: Learning How to Learn QSARs. MetaSel@PKDD/ECML 2015: 104-105 - 2014
- [j45]Larisa N. Soldatova, Daniel Nadis, Ross D. King, Piyali S. Basu, Emma Haddi, Véronique Baumlé, Nigel J. Saunders, Wolfgang Marwan, Brian B. Rudkin:
EXACT2: the semantics of biomedical protocols. BMC Bioinform. 15(S-14): S5 (2014) - [j44]Ross D. King, Chuan Lu:
An investigation into eukaryotic pseudouridine synthases. J. Bioinform. Comput. Biol. 12(4) (2014) - [c40]Fang Zhou, Claire Q, Ross D. King:
Predicting the Geographical Origin of Music. ICDM 2014: 1115-1120 - 2013
- [j43]Larisa N. Soldatova, Andrey Rzhetsky, Kurt De Grave, Ross D. King:
Representation of probabilistic scientific knowledge. J. Biomed. Semant. 4(S-1): S7 (2013) - 2012
- [c39]Tanveer A. Faruquie, Ashwin Srinivasan, Ross D. King:
Topic Models with Relational Features for Drug Design. ILP 2012: 45-57 - 2011
- [i2]Ross D. King:
Numbers as Data Structures: The Prime Successor Function as Primitive. CoRR abs/1104.3056 (2011) - [i1]George Macleod Coghill, Ross D. King, Ashwin Srinivasan:
Qualitative System Identification from Imperfect Data. CoRR abs/1111.0051 (2011) - 2010
- [j42]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:
Further developments towards a genome-scale metabolic model of yeast. BMC Syst. Biol. 4: 145 (2010) - [j41]Da Qi, Ross D. King, Andrew L. Hopkins, G. Richard J. Bickerton, Larisa N. Soldatova:
An Ontology for Description of Drug Discovery Investigations. J. Integr. Bioinform. 7(3) (2010) - [c38]Yihui Liu, Katherine Martin, Andrew Sparkes, Ross D. King:
The Analysis of Yeast Cell Morphology Using a Robot Scientist. CIS 2010: 10-14 - [c37]Oliver Ray, Ken E. Whelan, Ross D. King:
Logic-Based Steady-State Analysis and Revision of Metabolic Networks with Inhibition. CISIS 2010: 661-666 - [p3]Ross D. King, Amanda C. Schierz, Amanda Clare, Jem J. Rowland, Andrew Sparkes, Siegfried Nijssen, Jan Ramon:
Inductive Queries for a Drug Designing Robot Scientist. Inductive Databases and Constraint-Based Data Mining 2010: 425-451
2000 – 2009
- 2009
- [j40]Chuan Lu, Ross D. King:
An investigation into the population abundance distribution of mRNAs, proteins, and metabolites in biological systems. Bioinform. 25(16): 2020-2027 (2009) - [j39]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:
The Robot Scientist Adam. Computer 42(8): 46-54 (2009) - [c36]Oliver Ray, Ken E. Whelan, Ross D. King:
A Nonmonotonic Logical Approach for Modelling and Revising Metabolic Networks. CISIS 2009: 825-829 - [c35]Oliver Ray, Ken E. Whelan, Ross D. King:
Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data. ILP 2009: 194-201 - [c34]Amanda C. Schierz, Ross D. King:
Drugs and Drug-Like Compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds. PRIB 2009: 331-343 - 2008
- [j38]Ken E. Whelan, Ross D. King:
Using a logical model to predict the growth of yeast. BMC Bioinform. 9 (2008) - [j37]George Macleod Coghill, Ashwin Srinivasan, Ross D. King:
Qualitative System Identification from Imperfect Data. J. Artif. Intell. Res. 32: 825-877 (2008) - [j36]Ashwin Srinivasan, Ross D. King:
Incremental Identification of Qualitative Models of Biological Systems using Inductive Logic Programming. J. Mach. Learn. Res. 9: 1475-1533 (2008) - [c33]Ross D. King, Larisa N. Soldatova:
Formalising Phylogenetic Experiments: Ontologies and Logical Inference. AAAI Spring Symposium: Symbiotic Relationships between Semantic Web and Knowledge Engineering 2008: 59-62 - [c32]Larisa N. Soldatova, Wayne Aubrey, Ross D. King, Amanda Clare:
The EXACT description of biomedical protocols. ISMB 2008: 295-303 - 2007
- [j35]Michael C. Riley, Amanda Clare, Ross D. King:
Locational distribution of gene functional classes in Arabidopsis thaliana. BMC Bioinform. 8 (2007) - [c31]Robert Burbidge, Jem J. Rowland, Ross D. King, Nicholas T. Form, Benjamin J. Whitaker:
Evolutionary Optimization of Three-Photon Absorption in Molecular Iodine. CIDM 2007: 96-100 - [c30]Robert Burbidge, Jem J. Rowland, Ross D. King:
Active Learning for Regression Based on Query by Committee. IDEAL 2007: 209-218 - [p2]Simon M. Garrett, George Macleod Coghill, Ashwin Srinivasan, Ross D. King:
Learning Qualitative Models of Physical and Biological Systems. Computational Discovery of Scientific Knowledge 2007: 248-272 - [p1]Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe:
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics. Computational Discovery of Scientific Knowledge 2007: 273-289 - 2006
- [j34]Amanda Clare, Andreas Karwath, Helen Ougham, Ross D. King:
Functional bioinformatics for Arabidopsis thaliana. Bioinform. 22(9): 1130-1136 (2006) - [j33]Amanda Clare, Andreas Karwath, Helen Ougham, Ross D. King:
Functional bioinformatics for Arabidopsis thaliana. Bioinform. 22(13): 1674 (2006) - [j32]Bård Buttingsrud, Einar Ryeng, Ross D. King, Bjørn K. Alsberg:
Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships. J. Comput. Aided Mol. Des. 20(6): 361-373 (2006) - [j31]Sébastien Ferré, Ross D. King:
Finding Motifs in Protein Secondary Structure for Use in Function Prediction. J. Comput. Biol. 13(3): 719-731 (2006) - [j30]Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King:
Quantitative pharmacophore models with inductive logic programming. Mach. Learn. 64(1-3): 65-90 (2006) - [j29]Rui Camacho, Ross D. King, Ashwin Srinivasan:
Guest editorial. Mach. Learn. 64(1-3): 145-147 (2006) - [c29]Larisa N. Soldatova, Amanda Clare, Andrew Sparkes, Ross D. King:
An ontology for a Robot Scientist. ISMB (Supplement of Bioinformatics) 2006: 464-471 - 2005
- [j28]Ross D. King, Simon M. Garrett, George Macleod Coghill:
On the use of qualitative reasoning to simulate and identify metabolic pathway. Bioinform. 21(9): 2017-2026 (2005) - [j27]Sébastien Ferré, Ross D. King:
A Dichotomic Search Algorithm for Mining and Learning in Domain-Specific Logics. Fundam. Informaticae 66(1-2): 1-32 (2005) - [c28]Ross D. King:
The Robot Scientist Project. ALT 2005: 12 - [c27]Ross D. King, Michael Young, Amanda Clare, Kenneth Whelan, Jem J. Rowland:
The Robot Scientist Project. Discovery Science 2005: 16-25 - 2004
- [j26]Ross D. King:
Applying Inductive Logic Programming to Predicting Gene Function. AI Mag. 25(1): 57-68 (2004) - [j25]Ross D. King, Paul H. Wise, Amanda Clare:
Confirmation of data mining based predictions of protein function. Bioinform. 20(7): 1110-1118 (2004) - [c26]George Macleod Coghill, Simon M. Garrett, Ross D. King:
Learning Qualitative Metabolic Models. ECAI 2004: 445-449 - [c25]Sébastien Ferré, Ross D. King:
BLID: An Application of Logical Information Systems to Bioinformatics. ICFCA 2004: 47-54 - [c24]Ross D. King, Mohammed Ouali:
Poly-transformation. IDEAL 2004: 99-107 - [e1]Rui Camacho, Ross D. King, Ashwin Srinivasan:
Inductive Logic Programming, 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings. Lecture Notes in Computer Science 3194, Springer 2004, ISBN 3-540-22941-8 [contents] - 2003
- [j24]Hannu Toivonen, Ashwin Srinivasan, Ross D. King, Stefan Kramer, Christoph Helma:
Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001. Bioinform. 19(10): 1183-1193 (2003) - [j23]Ashwin Srinivasan, Ross D. King, Michael Bain:
An Empirical Study of the Use of Relevance Information in Inductive Logic Programming. J. Mach. Learn. Res. 4: 369-383 (2003) - [c23]Amanda Clare, Ross D. King:
Predicting gene function in Saccharomyces cerevisiae. ECCB 2003: 42-49 - [c22]Ross D. King:
A Personal View of How Best to Apply ILP. ILP 2003: 1 - [c21]Amanda Clare, Ross D. King:
Data Mining the Yeast Genome in a Lazy Functional Language. PADL 2003: 19-36 - [c20]David P. Enot, Ross D. King:
Application of Inductive Logic Programming to Structure-Based Drug Design. PKDD 2003: 156-167 - 2002
- [j22]Amanda Clare, Ross D. King:
Machine learning of functional class from phenotype data. Bioinform. 18(1): 160-166 (2002) - [j21]Andreas Karwath, Ross D. King:
Homology Induction: the use of machine learning to improve sequence similarity searches. BMC Bioinform. 3: 11 (2002) - [j20]Amanda Clare, Ross D. King:
How well do we understand the clusters found in microarray data? Silico Biol. 2(4): 511-522 (2002) - [c19]Janet Taylor, Ross D. King, Thomas Altmann, Oliver Fiehn:
Application of metabolomics to plant genotype discrimination using statistics and machine learning. ECCB 2002: 241-248 - 2001
- [j19]Christoph Helma, Ross D. King, Stefan Kramer, Ashwin Srinivasan:
The Predictive Toxicology Challenge 2000-2001. Bioinform. 17(1): 107-108 (2001) - [j18]Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe:
The utility of different representations of protein sequence for predicting functional class. Bioinform. 17(5): 445-454 (2001) - [j17]Christopher H. Bryant, Stephen H. Muggleton, Stephen G. Oliver, Douglas B. Kell, Philip G. K. Reiser, Ross D. King:
Combining Inductive Logic Programming, Active Learning and Robotics to Discover the Function of Genes. Electron. Trans. Artif. Intell. 5(B): 1-36 (2001) - [j16]Ross D. King, Nathalie Marchand-Geneste, Bjørn K. Alsberg:
A quantum mechanics based representation of molecules for machine inference. Electron. Trans. Artif. Intell. 5(B): 127-142 (2001) - [j15]Philip G. K. Reiser, Ross D. King, Douglas B. Kell, Stephen H. Muggleton, Christopher H. Bryant, Stephen G. Oliver:
Developing a Logical Model of Yeast Metabolism. Electron. Trans. Artif. Intell. 5(B): 223-244 (2001) - [j14]Ross D. King, Ashwin Srinivasan, Luc Dehaspe:
Warmr: a data mining tool for chemical data. J. Comput. Aided Mol. Des. 15(2): 173-181 (2001) - [c18]Andreas Karwath, Ross D. King:
An Automated ILP Server in the Field of Bioinformatics. ILP 2001: 91-103 - [c17]Amanda Clare, Ross D. King:
Knowledge Discovery in Multi-label Phenotype Data. PKDD 2001: 42-53 - 2000
- [c16]Ross D. King, Andreas Karwath, Amanda Clare, Luc Dehaspe:
Genome scale prediction of protein functional class from sequence using data mining. KDD 2000: 384-389
1990 – 1999
- 1999
- [j13]Ashwin Srinivasan, Ross D. King:
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes. Data Min. Knowl. Discov. 3(1): 37-57 (1999) - [c15]Ashwin Srinivasan, Ross D. King, Douglas W. Bristol:
An assessment of submissions made to the Predictive Toxicology Evaluation Challenge. IJCAI 1999: 270-275 - [c14]Ashwin Srinivasan, Ross D. King, Douglas W. Bristol:
An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment. ILP 1999: 291-302 - 1998
- [j12]Ross D. King, Ashwin Srinivasan:
The discovery of indicator variables for QSAR using inductive logic programming. J. Comput. Aided Mol. Des. 12(6): 571-580 (1998) - [c13]Stephen H. Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg:
Biochemical Knowledge Discovery Using Inductive Logic Programming. Discovery Science 1998: 326-341 - [c12]Luc Dehaspe, Hannu Toivonen, Ross D. King:
Finding Frequent Substructures in Chemical Compounds. KDD 1998: 30-36 - 1997
- [j11]Ross D. King, Mansoor A. S. Saqi, Roger A. Sayle, Michael J. E. Sternberg:
DSC: public domain protein secondary structure predication. Comput. Appl. Biosci. 13(4): 473-474 (1997) - [j10]Ross D. King, Ashwin Srinivasan:
The discovery of indicator variables for QSAR using inductive logic programming. J. Comput. Aided Mol. Des. 11(6): 571-580 (1997) - [c11]Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg:
The Predictive Toxicology Evaluation Challenge. IJCAI (1) 1997: 4-9 - [c10]Ashwin Srinivasan, Ross D. King, Stephen H. Muggleton, Michael J. E. Sternberg:
Carcinogenesis Predictions Using ILP. ILP 1997: 273-287 - 1996
- [j9]Ashwin Srinivasan, Stephen H. Muggleton, Michael J. E. Sternberg, Ross D. King:
Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction. Artif. Intell. 85(1-2): 277-299 (1996) - [j8]Ross D. King, C. G. Angus:
PM - protein music. Comput. Appl. Biosci. 12(3): 251-252 (1996) - [c9]Ashwin Srinivasan, Ross D. King:
Feature Construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity by Structural Attributes. Inductive Logic Programming Workshop 1996: 89-104 - 1995
- [j7]Ross D. King:
Comparison of artificial intelligence methods for modeling pharmaceutical QSARS. Appl. Artif. Intell. 9(2): 213-233 (1995) - [j6]Ross D. King, Cao Feng, A. Sutherland:
STALOG: Comparison of classification algorithms on large real-world problems. Appl. Artif. Intell. 9(3): 289-333 (1995) - [j5]Ross D. King, Michael J. E. Sternberg, Ashwin Srinivasan:
Relating Chemical Activity to Structure: An Examination of ILP Successes. New Gener. Comput. 13(3&4): 411-433 (1995) - [c8]