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Ross 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
- 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) - [i8]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) - [i7]Stefan Kramer, Mattia Cerrato, Saso Dzeroski, Ross D. King:
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems. CoRR abs/2305.02251 (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]Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen H. Muggleton:
Drug Design by Machine Learning. Machine Intelligence 15 1995: 328-338 - 1994
- [j4]Jonathan D. Hirst
, Ross D. King
, Michael J. E. Sternberg
:
Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines. J. Comput. Aided Mol. Des. 8(4): 405-420 (1994) - [j3]Jonathan D. Hirst
, Ross D. King
, Michael J. E. Sternberg
:
Quantitative structure-activity relationships by neural networks and inductive logic programming. II. The inhibition of dihydrofolate reductase by triazines. J. Comput. Aided Mol. Des. 8(4): 421-432 (1994) - [j2]Ross D. King:
Inductive logic programming: techniques and applications by Nada Lavrac and Saso Dzeroski, Ellis Horwood, UK, 1993, pp 293, £39.95, ISBN 0-13-457870-8. Knowl. Eng. Rev. 9(3): 311-312 (1994) - [j1]Ivan Bratko, Ross D. King:
Applications of Inductive Logic Programming. SIGART Bull. 5(1): 43-49 (1994) - [c7]Ross D. King, Dominic A. Clark, Jack Shirazi, Michael J. E. Sternberg:
Inductive Logic Programming Used to Discover Topological Constraints in Protein Structures. ISMB 1994: 219-226 - 1993
- [c6]Ross D. King, Dominic A. Clark, Jack Shirazi, Michael J. E. Sternberg:
Discovery of Protein Structural Constraints in a Deductive Database using Inductive Logic Programming. Machine Intelligence 14 1993: 275-302 - 1992
- [c5]A. Sutherland, Bob Henery, Rafael Molina, Charles C. Taylor, Ross D. King:
Statistical Methods in Learning. IPMU 1992: 173-182 - [c4]Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen H. Muggleton:
Machine Learning and biomolecular modelling. Machine Intelligence 13 1992: 193-212 - [c3]Ross D. King, Bob Henery, Cao Feng, A. Sutherland:
A Comparative Study of Classification Algorithms: Statistical, Machine Learning and Neural Network. Machine Intelligence 13 1992: 311-359 - 1991
- [c2]Steffen Schulze-Kremer, Ross D. King:
IPSA: Inductive Protein Structure Analysis. EWSL 1991: 513
1980 – 1989
- 1987
- [c1]Ross D. King:
An Inductive Learning Approach to the Problem of Predicting a Protein's Secondary Structure from Its Amino Acid Sequence. EWSL 1987: 230-250