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Jonathan D. Hirst
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2020 – today
- 2024
- [j40]Joseph Heeley
, Samuel Boobier
Solvent flashcards: a visualisation tool for sustainable chemistry. J. Cheminformatics 16(1): 60 (2024) - [j39]Toby E. King
Optimizing Excipient Properties to Prevent Aggregation in Biopharmaceutical Formulations. J. Chem. Inf. Model. 64(1): 265-275 (2024) - [j38]Shayantan Chaudhuri
Quantum Chemical Characterization of Rotamerism in Thio-Michael Additions for Targeted Covalent Inhibitors. J. Chem. Inf. Model. 64(19): 7687-7697 (2024) - [c7]Yu Liu, Lihui Duo, Jonathan D. Hirst, Jianfeng Ren, Bencan Tang, Dave Towey
Three-Branch Molecular Representation Learning Framework for Predicting Molecular Properties in Drug Discovery. COMPSAC 2024: 1983-1989 - 2023
- [j37]Samuel Boobier
AI4Green: An Open-Source ELN for Green and Sustainable Chemistry. J. Chem. Inf. Model. 63(10): 2895-2901 (2023) - 2022
- [j36]Samuel J. H. Gaughan
Effect of Oriented Electric Fields on Biologically Relevant Iron-Sulfur Clusters: Tuning Redox Reactivity for Catalysis. J. Chem. Inf. Model. 62(3): 591-601 (2022) - [j35]Ellen E. Guest
Alchemical Free Energy Methods Applied to Complexes of the First Bromodomain of BRD4. J. Chem. Inf. Model. 62(6): 1458-1470 (2022) - [j34]Alexe L. Haywood
Kernel Methods for Predicting Yields of Chemical Reactions. J. Chem. Inf. Model. 62(9): 2077-2092 (2022) - 2020
- [j33]Ellen E. Guest, Steven A. Oatley, Simon J. F. Macdonald, Jonathan D. Hirst
Molecular Simulation of αvβ6 Integrin Inhibitors. J. Chem. Inf. Model. 60(11): 5487-5498 (2020)
2010 – 2019
- 2017
- [j32]Jonathan D. Hirst, Wonpil Im, Joan-Emma Shea:
Simulating Biomolecules: Festschrift to commemorate the 60th birthday of Charles L. Brooks III. J. Comput. Chem. 38(15): 1111-1113 (2017) - [j31]Fouad S. Husseini, David Robinson
Computing infrared spectra of proteins using the exciton model. J. Comput. Chem. 38(16): 1362-1375 (2017) - [j30]Christian J. Suess, Jonathan D. Hirst
Quantum chemical calculations of tryptophan → heme electron and excitation energy transfer rates in myoglobin. J. Comput. Chem. 38(17): 1495-1502 (2017) - 2011
- [j29]David Robinson
Water order profiles on phospholipid/cholesterol membrane bilayer surfaces. J. Comput. Chem. 32(12): 2613-2618 (2011) - [j28]Abrar Hussain, Peter E. Shaw
Molecular dynamics simulations and in silico peptide ligand screening of the Elk-1 ETS domain. J. Cheminformatics 3: 49 (2011) - 2010
- [j27]Pooja Jain
Automatic structure classification of small proteins using random forest. BMC Bioinform. 11: 364 (2010) - [j26]Petros Kountouris
Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures. BMC Bioinform. 11: 407 (2010) - [j25]Robert Elliott Smith, Max Kun Jiang, Jaume Bacardit
A learning classifier system with mutual-information-based fitness. Evol. Intell. 3(1): 31-50 (2010) - [j24]Abrar Hussain, James L. Melville, Jonathan D. Hirst
Molecular docking and QSAR of aplyronine A and analogues: potent inhibitors of actin. J. Comput. Aided Mol. Des. 24(1): 1-15 (2010)
2000 – 2009
- 2009
- [j23]Benjamin M. Bulheller, Jonathan D. Hirst
DichroCalc - circular and linear dichroism online. Bioinform. 25(4): 539-540 (2009) - [j22]Jaume Bacardit
Automated Alphabet Reduction for Protein Datasets. BMC Bioinform. 10 (2009) - [j21]Petros Kountouris
Prediction of backbone dihedral angles and protein secondary structure using support vector machines. BMC Bioinform. 10: 437 (2009) - [j20]Pooja Jain, Jonathan M. Garibaldi
Supervised machine learning algorithms for protein structure classification. Comput. Biol. Chem. 33(3): 216-223 (2009) - [j19]Benson M. Spowage, Craig L. Bruce, Jonathan D. Hirst
Interpretable correlation descriptors for quantitative structure-activity relationships. J. Cheminformatics 1: 22 (2009) - [j18]Michael Stout, Jaume Bacardit
Prediction of topological contacts in proteins using learning classifier systems. Soft Comput. 13(3): 245-258 (2009) - 2008
- [j17]Michael Stout, Jaume Bacardit
Prediction of recursive convex hull class assignments for protein residues. Bioinform. 24(7): 916-923 (2008) - [j16]Stephen E. Hamby, Jonathan D. Hirst
Prediction of glycosylation sites using random forests. BMC Bioinform. 9 (2008) - [p1]Jaume Bacardit
Data Mining in Proteomics with Learning Classifier Systems. Learning Classifier Systems in Data Mining 2008: 17-46 - 2007
- [j15]Daniel Barthel, Jonathan D. Hirst
ProCKSI: a decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information. BMC Bioinform. 8 (2007) - [j14]James L. Melville, Jenna F. Riley, Jonathan D. Hirst
Similarity by Compression. J. Chem. Inf. Model. 47(1): 25-33 (2007) - [j13]Craig L. Bruce, James L. Melville, Stephen D. Pickett, Jonathan D. Hirst
Contemporary QSAR Classifiers Compared. J. Chem. Inf. Model. 47(1): 219-227 (2007) - [j12]James L. Melville, Jonathan D. Hirst
TMACC: Interpretable Correlation Descriptors for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 47(2): 626-634 (2007) - [c6]Jaume Bacardit
Automated alphabet reduction method with evolutionary algorithms for protein structure prediction. GECCO 2007: 346-353 - 2006
- [c5]Michael Stout, Jaume Bacardit
From HP Lattice Models to Real Proteins: Coordination Number Prediction Using Learning Classifier Systems. EvoWorkshops 2006: 208-220 - [c4]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 - 2005
- [j11]David A. Pelta
A fuzzy sets based generalization of contact maps for the overlap of protein structures. Fuzzy Sets Syst. 152(1): 103-123 (2005) - [j10]Mark T. Oakley
Lattice models of peptide aggregation: Evaluation of conformational search algorithms. J. Comput. Chem. 26(15): 1638-1646 (2005) - [j9]T. John McNeany, Jonathan D. Hirst
Inhibition of the Tyrosine Kinase, Syk, Analyzed by Stepwise Nonparametric Regression. J. Chem. Inf. Model. 45(3): 768-776 (2005) - [j8]James L. Melville, Kevin R. J. Lovelock, Claire Wilson
Exploring Phase-Transfer Catalysis with Molecular Dynamics and 3D/4D Quantitative Structure-Selectivity Relationships. J. Chem. Inf. Model. 45(4): 971-981 (2005) - 2004
- [j7]Matthew J. Wood, Jonathan D. Hirst
Predicting protein secondary structure by cascade-correlation neural networks. Bioinform. 20(3): 419-420 (2004) - [j6]James L. Melville, Jonathan D. Hirst
On the Stability of CoMFA Models. J. Chem. Inf. Model. 44(4): 1294-1300 (2004) - [c3]Matthew J. Wood, Jonathan D. Hirst
Recent Applications of Neural Networks in Bioinformatics. WIRN 2004: 91-97 - 2002
- [c2]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 - [c1]Natalio Krasnogor, B. P. Blackburne, Edmund K. Burke, Jonathan D. Hirst:
Multimeme Algorithms for Protein Structure Prediction. PPSN 2002: 769-778 - 2000
- [j5]Pere Constans, Jonathan D. Hirst
Nonparametric Regression Applied to Quantitative Structure-Activity Relationships. J. Chem. Inf. Comput. Sci. 40(2): 452-459 (2000)
1990 – 1999
- 1998
- [j4]Michal Vieth, Jonathan D. Hirst, Andrzej Kolinski, Charles L. Brooks III:
Assessing energy functions for flexible docking. J. Comput. Chem. 19(14): 1612-1622 (1998) - [j3]Michal Vieth, Jonathan D. Hirst, Brian N. Dominy, Heidi Daigler, Charles L. Brooks III:
Assessing search strategies for flexible docking. J. Comput. Chem. 19(14): 1623-1631 (1998) - 1994
- [j2]Jonathan D. Hirst
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) - [j1]Jonathan D. Hirst
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)
Coauthor Index
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