Jonathan D. Hirst

David Robinson, Nicholas A. Besley, Paul O'shea, Jonathan D. Hirst: Water order profiles on phospholipid/cholesterol membrane bilayer surfaces. Journal of Computational Chemistry 32(12): 2613-2618 (2011)

Abrar Hussain, Peter E. Shaw, Jonathan D. Hirst: Molecular dynamics simulations and in silico peptide ligand screening of the Elk-1 ETS domain. J. Cheminformatics 3: 49 (2011)

Pooja Jain, Jonathan D. Hirst: Automatic structure classification of small proteins using random forest. BMC Bioinformatics 11: 364 (2010)

Petros Kountouris, Jonathan D. Hirst: Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures. BMC Bioinformatics 11: 407 (2010)

Robert Elliott Smith, Max Kun Jiang, Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst: A learning classifier system with mutual-information-based fitness. Evolutionary Intelligence 3(1): 31-50 (2010)

Abrar Hussain, James L. Melville, Jonathan D. Hirst: Molecular docking and QSAR of aplyronine A and analogues: potent inhibitors of actin. Journal of Computer-Aided Molecular Design 24(1): 1-15 (2010)

Benjamin M. Bulheller, Jonathan D. Hirst: DichroCalc - circular and linear dichroism online. Bioinformatics 25(4): 539-540 (2009)

Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Alfonso Valencia, Robert Elliott Smith, Natalio Krasnogor: Automated Alphabet Reduction for Protein Datasets. BMC Bioinformatics 10 (2009)

Petros Kountouris, Jonathan D. Hirst: Prediction of backbone dihedral angles and protein secondary structure using support vector machines. BMC Bioinformatics 10: 437 (2009)

Pooja Jain, Jonathan M. Garibaldi, Jonathan D. Hirst: Supervised machine learning algorithms for protein structure classification. Computational Biology and Chemistry 33(3): 216-223 (2009)

Benson M. Spowage, Craig L. Bruce, Jonathan D. Hirst: Interpretable correlation descriptors for quantitative structure-activity relationships. J. Cheminformatics 1: 22 (2009)

Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Robert Elliott Smith, Natalio Krasnogor: Prediction of topological contacts in proteins using learning classifier systems. Soft Comput. 13(3): 245-258 (2009)

Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor: Prediction of recursive convex hull class assignments for protein residues. Bioinformatics 24(7): 916-923 (2008)

Stephen E. Hamby, Jonathan D. Hirst: Prediction of glycosylation sites using random forests. BMC Bioinformatics 9 (2008)

Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Natalio Krasnogor: Data Mining in Proteomics with Learning Classifier Systems. Learning Classifier Systems in Data Mining 2008: 17-46

Daniel Barthel, Jonathan D. Hirst, Jacek Blazewicz, Edmund K. Burke, Natalio Krasnogor: ProCKSI: a decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information. BMC Bioinformatics 8 (2007)

Jaume Bacardit, Michael Stout, Jonathan D. Hirst, Kumara Sastry, Xavier Llorà, Natalio Krasnogor: Automated alphabet reduction method with evolutionary algorithms for protein structure prediction. GECCO 2007: 346-353

Michael Stout, Jaume Bacardit, Jonathan D. Hirst, Natalio Krasnogor, Jacek Blazewicz: From HP Lattice Models to Real Proteins: Coordination Number Prediction Using Learning Classifier Systems. EvoWorkshops 2006: 208-220

Jaume Bacardit, Michael Stout, Natalio Krasnogor, Jonathan D. Hirst, Jacek Blazewicz: Coordination number prediction using learning classifier systems: performance and interpretability. GECCO 2006: 247-254

David A. Pelta, Natalio Krasnogor, Carlos Bousoño-Calzón, José L. Verdegay, Jonathan D. Hirst, Edmund K. Burke: A fuzzy sets based generalization of contact maps for the overlap of protein structures. Fuzzy Sets and Systems 152(1): 103-123 (2005)

Mark T. Oakley, Jonathan M. Garibaldi, Jonathan D. Hirst: Lattice models of peptide aggregation: Evaluation of conformational search algorithms. Journal of Computational Chemistry 26(15): 1638-1646 (2005)

T. John McNeany, Jonathan D. Hirst: Inhibition of the Tyrosine Kinase, Syk, Analyzed by Stepwise Nonparametric Regression. Journal of Chemical Information and Modeling 45(3): 768-776 (2005)

James L. Melville, Kevin R. J. Lovelock, Claire Wilson, Bryan Allbutt, Edmund K. Burke, Barry Lygo, Jonathan D. Hirst: Exploring Phase-Transfer Catalysis with Molecular Dynamics and 3D/4D Quantitative Structure-Selectivity Relationships. Journal of Chemical Information and Modeling 45(4): 971-981 (2005)

Matthew J. Wood, Jonathan D. Hirst: Predicting protein secondary structure by cascade-correlation neural networks. Bioinformatics 20(3): 419-420 (2004)

James L. Melville, Jonathan D. Hirst: On the Stability of CoMFA Models. Journal of Chemical Information and Modeling 44(4): 1294-1300 (2004)

Matthew J. Wood, Jonathan D. Hirst: Recent Applications of Neural Networks in Bioinformatics. WIRN 2004: 91-97

Robert D. Carr, William E. Hart, Natalio Krasnogor, Jonathan D. Hirst, Edmund K. Burke, James Smith: Alignment Of Protein Structures With A Memetic Evolutionary Algorithm. GECCO 2002: 1027-1034

Natalio Krasnogor, B. P. Blackburne, Edmund K. Burke, Jonathan D. Hirst: Multimeme Algorithms for Protein Structure Prediction. PPSN 2002: 769-778

Pere Constans, Jonathan D. Hirst: Nonparametric Regression Applied to Quantitative Structure-Activity Relationships. Journal of Chemical Information and Computer Sciences 40(2): 452-459 (2000)

Michal Vieth, Jonathan D. Hirst, Andrzej Kolinski, Charles L. Brooks III: Assessing energy functions for flexible docking. Journal of Computational Chemistry 19(14): 1612-1622 (1998)

Michal Vieth, Jonathan D. Hirst, Brian N. Dominy, Heidi Daigler, Charles L. Brooks III: Assessing search strategies for flexible docking. Journal of Computational Chemistry 19(14): 1623-1631 (1998)

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. Journal of Computer-Aided Molecular Design 8(4): 405-420 (1994)

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. Journal of Computer-Aided Molecular Design 8(4): 421-432 (1994)