Academic Publications

Articles (54)

  • Poursharif, G., Brint, A., Holliday, J., Black, M., & Marshall M. (2018). Low Voltage Current Estimation Using AMI/Smart Meter Data. International Journal of Electrical Power & Energy Systems 99, 290-298.
  • Duesbury, E., Holliday, J., & Willett, P. (2018). Comparison of Maximum Common Subgraph Isomorphism Algorithms for the Alignment of 2D Chemical Structures. ChemMedChem, 13, 588-598. (doi:10.1002/cmdc.201700482).
  • Holliday, J.D., Sani, N., & Willett, P. (2016). Ligand-based virtual screening using a genetic algorithm with data fusion. MATCH Communications in Mathematical and in Computational Chemistry. 80 (2018) 623-638.
  • Franco, P., Porta, N., Holliday, J. D., & Willett, P. (2017). Molecular similarity considerations in the licensing of orphan drugs. Drug Discovery Today, 22:2, 377-381. (doi: 10.1016/j.drudis.2016.11.024).
  • Gillet, V., Holliday, J., & Willett, P. (2015). Chemoinformatics at the University of Sheffield 2002-2014. Molecular Informatics, 34:9, 598-607. (doi: 10.1002/minf.201500004).
  • Duesbury, E., Holliday, J.D., & Willett, P. (2015). Maximum common substructure-based data fusion in similarity searching. Journal of Chemical Information and Modeling, 55:2, 222-230. (doi: 10.1021/ci5005702).
  • Holliday, J.D., Sani, N. & Willett, P. (2015). Calculation of substructural analysis weights using a genetic algorithm. Journal of Chemical Information and Modeling, 55:2, 214-221. (doi: 10.1021/ci500540s).
  • Franco, P., Porta, N., Holliday, J.D. & Willett, P. (2014). The use of 2D fingerprint methods to support the assessment of similarity in orphan drug legislation. Journal of Cheminformatics, 6:5. (doi:10.1186/1758-2946-6-5, web: www.jcheminf.com/content/6/1/5)
  • Arif, S.M., Holliday, J.D. & Willett, P. (2013). Comparison of chemical similarity measures using different numbers of query structures. Journal of Information Science, 39:1, 7-14. (doi: 10.1177/0165551512470042).
  • Holliday, J., Upton, C., Thompson, A., Robinson, J., Herring, J., Gilbert, H. & Norman, P. (2013). Geographical analysis of the vernacular. Journal of Information Science, 39:1, 26-35. (doi: 10.1177/0165551512470049)
  • Todeschini, R., Consonni, V., Xiang, H., Holliday, J.D., Buscema, M. & Willett, P. (2012). Similarity coefficients for binary chemoinformatics data: overview and extended comparison using simulated and real datasets. Journal of Chemical Information and Modeling, 52(11), 2884-2901. (doi: 10.1021/ci30026)
  • Chu, C-W., Holliday, J.D. & Willett, P. (2012). Combining multiple classifications of chemical structures using consensus clustering. Bioorganic & Medicinal Chemistry, 20, 5366-5371. (doi:10.1016/j.bmc.2012.03.010)
  • Holliday, J.D., Willett, P. & Xiang, H. (2012). Interactions between weighting scheme and similarity coefficient in similarity-based virtual screening. International Journal of Chemoinformatics and Chemical Engineering, 2:2, 28-41.
  • Holliday, J.D., Kanoulas, E., Malim, N. & Willett, P. (2011). Multiple search methods for similarity-based virtual screening: Analysis of search overlap and precision. Journal of Cheminformatics, 3(1):29. (doi:10.1186/1758-2946-3-29).
  • Gardiner, E.J., Holliday, J.D., O’Dowd, C. & Willett, P. (2011). Effectiveness of 2D fingerprints for scaffold hopping. Future Medicinal Chemistry, 3(4), 405-414.
  • Arif, S.M., Holliday, J.D. & Willett, P. (2010). Inverse frequency weighting of fragments for similarity-based virtual screening. Journal of Chemical Information and Modeling, 50, 1340-1349.
  • Clark, R.D., Shepphird, J.K. & Holliday, J. (2009). The effect of structural redundancy in validation sets on virtual screening performance. Journal of Chemometrics, 23(9), 471-478.
  • Arif, S., Holliday, J.D. & Willett, P. (2009). Analysis and use of fragment occurrence data in similarity-based virtual screening. Journal of Computer-Aided Molecular Design, 23, 655-668.
  • Chu, C.-W., Holliday, J. & Willett, P. (2009). Effect of data standardization on the clustering of chemical structures. Journal of Chemical Information and Modeling, 49, 155-161.
  • Chen, J., Holliday, J. & Bradshaw, J. (2009). A machine learning approach to weighting schemes in the data fusion of similarity coefficients. Journal of Chemical Information and Modeling, 49, 185-194.
  • Gardiner, E.J., Gillet, V.J., Haranczyk, M., Hert, J., Holliday, J.D., Malim, N., Patel, Y. & Willett, P. (2009). Turbo similarity searching: effect of fingerprint and dataset on virtual-screening performance. Statistical Analysis and Data Mining, 2(2), 103-114.
  • Al Khalifa, A., Haranczyck, M. & Holliday, J. (2009). Comparison of non-binary similarity coefficients for similarity searching, clustering and compound selection. Journal of Chemical Information and Modeling, 49, 1193-1201.
  • Holliday, J.D. & Willett, P. (2008). The influence of the DARC project on chemoinformatics research at the University of Sheffield. Actualité Chimique (www.lactualitechimica.org), 320-321, 45-50.
  • Haranczyk, M. & Holliday, J. (2008). Comparison of similarity coefficients for clustering and compound selection. Journal of Chemical Information and Modeling, 48, 498-508.
  • Haranczyk, M., Holliday, J., Willett, P. & Gutowski, M. (2008). Structure and singly occupied molecular orbital analysis of anionic tautomers of guanine. Journal of Computational Chemistry, 29(8), 1277-1291.
  • Thompson, S.J., Hattotuwagama, C.K., Holliday, J.D. & Flower, D. (2006). On the hydrophobicity of peptides: comparing empirical prediction of peptide log P values. Bioinformation (www.bioinformation.net), 1(7), 237-241.
  • Hirons, L., Holliday, J.D., Jelfs, S.P., Willett, P. & Gedeck P. (2005). Use of the R-group descriptor for alignment-free QSAR. QSAR & Combinatorial Science, 24, 611-619.
  • Salim, N., Holliday, J. & Willett, P. (2004). On the significance of topological-indices based non-binary molecular similarity measures. Sains Malaysiana, 33(2), 157-172.
  • Holliday, J.D., Rodgers, S.L., Willett, P., Chen, M.-Y., Mahfouf, M., Lawson, K. & Mullier, G. (2004). Clustering files of chemical structures using the fuzzy k-means clustering method. Journal of Chemical Information and Computer Sciences, 44, 894-902.
  • Holliday, J.D., Jelfs, S.J., Willett, P. & Gedeck, P. (2003). Calculation of inter-substituent similarity using R-group descriptors. Journal of Chemical Information and Computer Sciences, 43, 406-411.
  • Holliday, J.D., Salim, N., Whittle, M. & Willett, P. (2003). Analysis and display of the size-dependence of chemical similarity coefficients. Journal of Chemical Information and Computer Sciences, 43, 819-828.
  • Salim, N., Holliday, J. & Willett, P. (2003). Combination of fingerprint-based similarity coefficients using data fusion. Journal of Chemical Information and Computer Sciences, 43, 435-442.
  • Bishop, N., Gillet, V.J., Holliday, J.D. & Willett, P. (2003). Chemoinformatics research at the University of Sheffield: a history and citation analysis. Journal of Information Sciences, 29, 249-267.
  • Ashton, M., Barnard, J., Casset, F., Charlton, M., Downs, G., Gorse, D., Holliday, J., Lahana, R. & Willett, P. (2002). Identification of diverse database subsets using property-based and fragment-based molecular descriptors. Quantitative Structure-Activity Relationships, 21, 598-604.
  • Holliday, J.D., Hu, C.-Y. & Willett, P. (2002). Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings. Combinatorial Chemistry and High-Throughput Screening, 5, 155-166.
  • Edgar, S.J., Holliday, J.D. & Willett, P. (2000). Effectiveness of retrieval in similarity searches of chemical databases: a review of performance measures. Journal of Molecular Graphics and Modelling, 18, 343-357.
  • Gardiner, E.J., Holliday, J.D., Willett, P., Wilton, D.J. & Artymiuk, P.J. (1998). Selection of reagents for combinatorial synthesis using clique detection. Quantitative Structure-Activity Relationships, 17, 232-236.
  • Holliday, J.D. & Willett, P. (1998). Using a genetic algorithm to identify common structural features in sets of ligands. Journal of Molecular Graphics and Modelling, 15, 221-232.
  • Holliday, J.D. & Willett, P. (1996). Definitions of ‘dissimilarity’ for dissimilarity-based compound selection. Journal of Biomolecular Screening, 1, 145-151.
  • Lynch, M.F. & Holliday, J.D. (1996). The Sheffield Generic Structures Project – a retrospective review. Journal of Chemical Information and Computer Sciences, 36, 930-936.
  • Holliday, J.D. & Lynch, M.F. (1995). Computer storage and retrieval of generic chemical structures in patents. Part 17. Evaluation of the refined search. Journal of Chemical Information and Computer Sciences, 35, 659-662.
  • Holliday, J.D. & Lynch, M.F. (1995). Computer storage and retrieval of generic chemical structures in patents. Part 16. The refined search: an algorithm for matching components of generic chemical structures at the atom-bond level. Journal of Chemical Information and Computer Sciences, 35, 1-7.
  • Holliday, J.D., Ranade, S.S. & Willett, P. (1995). A fast algorithm for selecting sets of dissimilar structures from large chemical databases. Quantitative Structure-Activity Relationships, 14, 501-506.
  • Holliday, J.D., Downs, G.M., Gillet, V.J., Lynch, M.F. & Dethlefsen, W. (1994). Evaluation of the screening stages of the Sheffield research project on computer storage and retrieval of generic chemical structures in patents. Journal of Chemical Information and Computer Sciences, 34, 39-46.
  • Holliday, J.D., Downs, G.M., Gillet, V.J. & Lynch, M.F. (1993). Computer storage and retrieval of generic chemical structures in patents. Part 15. Generation of topological fragment descriptors from non-topological representations of generic structures. Journal of Chemical Information and Computer Sciences, 33, 369-377.
  • Holliday, J.D., Downs, G.M., Gillet, V.J. & Lynch, M.F. (1992). Computer storage and retrieval of generic chemical structures in patents, Part 14. Fragment generation from generic structures. Journal of Chemical Information and Computer Sciences, 32, 453-462.
  • Dethlefsen, W., Lynch, M.F., Gillet, V.J., Downs, G.M., Holliday, J.D. & Barnard, J.M. (1991). Computer storage and retrieval of generic chemical structures in patents, Part 12. Principles of search operations involving parameter lists: matching-relations, user-defined match levels, and transition from the reduced graph search to the refined search. Journal of Chemical Information and Computer Sciences, 31, 253-260.
  • Dethlefsen, W., Lynch, M.F., Gillet, V.J., Downs, G.M., Holliday, J.D. & Barnard, J.M. (1991). Computer storage and retrieval of generic chemical structures in patents, Part 11. Theoretical aspects of the use of structure languages in a retrieval system. Journal of Chemical Information and Computer Sciences, 31, 233-253.
  • Gillet, V.J., Downs, G.M., Holliday, J.D., Lynch, M.F. & Dethlefsen, W. (1991). Computer storage and retrieval of generic chemical structures in patents, Part 13. Reduced graph generation. Journal of Chemical Information and Computer Sciences, 31, 260-270.
  • Holliday, J.D. (1991). Computer storage and retrieval of generic chemical structures in patents: fragment generation and screening of generic structures. PhD, University of Sheffield.
  • Downs, G.M., Gillet, V.J., Holliday, J.D. & Lynch, M.F. (1989). A review of ring perception algorithms for chemical graphs. Journal of Chemical Information and Computer Sciences, 29, 172-187.
  • Downs, G.M., Gillet, V.J., Holliday, J.D. & Lynch, M.F. (1989). Computer storage and retrieval of generic chemical structures in patents. Part 9. An algorithm to find the extended set of smallest rings (ESSR) in structurally explicit generics. Journal of Chemical Information and Computer Sciences, 29, 207-214.
  • Downs, G.M., Gillet, V.J., Holliday, J.D. & Lynch, M.F. (1989). Computer storage and retrieval of generic chemical structures in patents. Part 10. The generation and logical bubble-up of ring screens for structurally explicit generics. Journal of Chemical Information and Computer Sciences, 29, 215-221.
  • Downs, G.M., Gillet, V.J., Holliday, J.D. & Lynch, M.F. (1989). Theoretical aspects of ring perception and development of the extended set of smallest rings (ESSR) concept. Journal of Chemical Information and Computer Sciences, 29, 187-206.

Book Chapters (5)

  • Downs, G.M., Holliday, J.D. & Willett, P. (2017). Representing and searching of chemical information in patents. In: Lupu, M., Mayer, K., Kando, N. &  Trippe, A.J. (Eds). Current Challenges in Patent Information Retrieval – 2nd Edition, (pp 391-407), Springer. (doi: 10.1007/978-3-662-53817-3).
  • Arif, S.M., Holliday, J.D. & Willett, P. (2014). The use of weighted 2D fingerprints in similarity-based virtual screening. In: Basak, S.C. Restrepo, G. & Villaveces, J.L. (Eds). Advances in Mathematical Chemistry and Application, Vol 1, (pp 92-112), Bentham Science. (doi: 10.2174/97816080592871140101,
    web: ebooks.benthamscience.com/book/9781608059287/). Revised edition: Jan 2016, pp 92-112. (doi:10.1016/B978-1-68108-198-4.50005-9).
  • Holliday, J.D., Willett, P. & Xiang, H. (2013). Interactions between weighting scheme and similarity coefficient in similarity-based virtual screening. In: Haghi, A.K. (Ed). Methodologies and Applications for Chemoinformatics and Chemical Engineering, (pp 310-321), IGI Global. (doi: 10.4018/978-1-4666-4010-8).
  • Holliday, J. (2013). Voices dialectometry at the University of Sheffield. In: Upton, C. & Davies, B.L. (Eds). Analysing Twenty-first Century British English: Conceptual and Methodological Aspects of the Voices Project, (pp 198-207), Routledge.
  • Holliday, J.D. & Willett, P. (2011). Representing and searching of chemical-structure information in patents. In Lupo, M., Mayer. K., Tait, J. & Trippe, A.J. (Eds). Current Challenges in Patent Information Retrieval – 1st Edition, (pp 343-355), Springer.

Conference Proceedings (8)

  • Holliday, J.D., Sani, N., Willett, P. (2018). Ligand-Based Virtual Screening Using a Genetic Algorithm with Data Fusion. In: Restrepo, G. (Ed.), MATCH: Communications in Mathematical and in Computer Chemistry, 80(3) (Proceedings of “Mathematics in Chemistry Meeting”, Leipzig, October 26-28, 2016), pp. 623-638.
  • Poursharif, G., Brint, A., Holliday, J., Black, M. & Marshall, M. (2015). Smarter Business Processes resulting from Smart Data. Proceedings of the 23rd International Conference on Electricity Distribution, Lyon, France.
  • Poursharif, G., Brint, A., Holliday, J., Black, M. & Marshall, M. (2015). Geospatial visualization of Smart data for improved network management. In PowerTech, 2015 IEEE Eindhoven,  pp 1-6, IEEE. (doi:10.1109/PTC.2015.7232445).
  • Arif, S.M., Hert, J., Holliday, J.D., Malim, N. & Willett,P. (2009). Enhancing the effectiveness of fingerprint-based virtual screening: Use of turbo similarity searching and of fragment frequencies of occurrence. In Lecture Notes in Bioinformatics (Special Issue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics), pp 404-414, Springer.
  • Holliday, J.D., Salim, N. & Willett, P. (2005). On the magnitudes of coefficient values in the calculation of chemical similarity and dissimilarity. In: Lavine B. (Ed.), Chemometrics and Chemoinformatics: ACS Symposium Series 894, pp 77-95, American Chemical Society.
  • Gillet, V.J., Downs, J.M., Holliday, J., Lynch, M.F. & Dethlefsen, W. (1993). Searching a full generics database. In: Warr, W. A. (Ed.), Chemical Structures 2. The International Language of Chemistry, pp 88-102, Berlin: Springer Verlag.
  • Lynch, M.F., Downs, G.M., Gillet, V.J., Holliday, J.D. & Dethlefsen, W. (1989). Generic chemical structures in patents – an evaluation of the Sheffield University research work. In: Collier, H.R. (Ed.), Proceedings of the 1989 International Chemical Information Conference, Montreux, pp 161-173, Calne: Infonortics Ltd.
  • Downs, G.M., Gillet, V.J., Holliday, J.D. & Lynch, M.F. (1988). The Sheffield University generic chemical structures project – A review of progress and outstanding problems. In: Warr, W.A. (Ed.), Chemical Structures. The International language of Chemistry, pp 151-167. Berlin: Springer Verlag.

Presentations (8)

  • Holliday, J. Dealing with the Wealth of Open Source Data. Presented at the RSC CICAG meeting: “From Big Data to Chemical Information”, Royal Society of Chemistry, Piccadilly, London, April 2015.
  • Holliday, J. Mapping the BBC Voices. Presented at Advances in Visual Methods for Linguistics, University of York, September 2012.
  • Arif, S.M., Hert, J., Holliday, J.D., Malim, N. & Willett, P. Enhancing the Effectiveness of Fingerprint-Based Virtual Screening: Use of Turbo Similarity Searching and of Fragment Frequencies of Occurrence. Presented at the 4th IAPR International Conference on Pattern Recognition in Bioinformatics, City Hall, Sheffield, 2009.
  • Holliday, J., Al Khalifa, A., Arif, S., Haranczyk, M., Malim, N. & Willett, P. Recent Studies for Optimising Similarity-based Virtual Screening. Presented at the Optimizing Drug Design Workshop, Lorentz Center, Leiden, The Netherlands, July 2009.
  • Holliday, J.D., Choosing the Right Similarity Measure. Presented at the Daylight European User Group Meeting, Cambridge Garden Moat House, Cambridge, October 2005.
  • Holliday, J.D., Salim, N. & Willett, P. Combining similarity coefficients using data fusion. Presented at the UK Tripos User Group Meeting, Whittlebury Hall, Northamptonshire, February 2002.
  • Holliday, J.D. & Willett, P. New techniques for dissimilarity-based compound selection. Paper presented at the Fourth International Conference on Chemical Structures, Leeuwenhorst Congress Centre, Noordwijkerhout, The Netherlands, June 1996.
  • Holliday, J.D., Downs, G.M., Gillet, V.J., Lynch, M.F., & Dethlefsen, W. An evaluation of the screening stages of the Sheffield research project on computer storage and retrieval of generic chemical structures in patents. Paper presented at the Third International Conference on Chemical Structures, Leeuwenhorst Congress Centre, Noordwijkerhout, The Netherlands, June 1993.