Comparison of nonbinary similarity coefficients for similarity searching, clustering and compound selection

Journal of Chemical Information and Modeling

Volumn 49, Issue 5, 2009, Pages 1193-1201

  Khalifa, Aysha Al ^a   Haranczyk, Maciej ^a,b   Holliday, John ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL ENGINEERING; CHEMISTRY;

BINARY FINGERPRINTS; CHEMICAL DATABASE; COMPOUND SELECTION; DATABASE CLUSTERING; RELATIVE PERFORMANCE; SIMILARITY COEFFICIENTS; SIMILARITY SEARCHING; SUB-STRUCTURAL FRAGMENT;

PHYSICOCHEMICAL PROPERTIES;

EID: 66249099177     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci8004644     Document Type: Article

References (23)

1. Willett, P. Similarity methods in chemoinformatics. Ann. Rev. Inf. Sci. Technol. 2009, 43, 3-71.
2. Willett, P.; Barnard, J. M.; Downs, G. M. Chemical similarity searching. J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
3. Ellis, D.; Furner-Hines, J.; Willett, P. Measuring the degree of similarity between objects in text retrieval systems. Perspect. Inf. Manag. 1994, 3, 128-149.
4. Holliday, J. D.; Hu, C.-Y.; Willett, P. Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings. Comb. Chem. High Throughput Screen. 2002, 5, 155-166.
5. Holliday, J. D.; Salim, N.; Whittle, M.; Willett, P. Analysis and display of the size dependence of chemical similarity coefficients. J.Chem Inf. Comput. Sci. 2003, 43, 819-828.
6. Holliday, J. D.; Salim, N.; Willett, P. On the magnitudes of coefficient values in the calculation of chemical similarity and dissimilarity. In Chemometrics and Chemoinformatics; ACS symposium series 894; Lavine, B., Ed.; American Chemical Society: Washington, DC, 2005; pp 77-95.
7. Whittle, M.; Willett, P.; Klaffke, W.; van Noort, P. Evaluation of similarity measures for searching the Dictionary of Natural Products database. J. Chem. Inf. Comput. Sci. 2003, 43, 449-457.
8. Ginn, C. M. R.; Willett, P.; Bradshaw, J. Combination of molecular similarity measures using data fusion. Perspect. Drug Discovery Des. 2000, 20, 1-16.
9. Salim, N.; Holliday, J.; Willett, P. Combination of fingerprint-based similarity coefficients using data fusion. J Chem Inf Comput Scl. 2003, 43, 435-442.
10. Chen, J.; Holliday, J.; Bradshaw, J. A machine learning approach to weighting schemes in the data fusion of similarity coefficients. J. Chem. Inf. Model. 2009, 49, 185-194.
11. Haranczyk, M.; Holliday, J. Comparison of similarity coefficients for clustering and compound selection. J. Chem. Inf. Model. 2008, 48,498-508.
12. Concepts and Applications of Molecular Similarity; Johnson, M. A., Maggiora, G. M., Eds., John Wiley and Sons: New York, 1990.
13. Ward, J. H. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 1963, 58, 236-244.
14. Similarity and Clustering in Chemical Information Systems; Willett, P., Ed.; Research Studies Press: Letchworth, U.K., 1987.
15. Jarvis, R. A.; Patrick, E. A. Clustering using a similarity measure based on shard nearest neighbours. IEEE Trans. Comput. 1973, C-22, 1025-1034.
16. Chu, C.-W.; Holliday, J. D.; Willett, P. Effect of standardization on chemical clustering and similarity searching. J. Chem. Inf. Model. 2009, 49, 155-161.
17. Lajiness, M. S. Dissimilarity-based compound selection techniques. Perspect. Drug Discovery Des. 1997, 78, 65-84.
18. Fligner, M. A.; Verducci, J. S.; Blower, P. E. A modification of the Jaccard-Tanimoto similarity index for diverse selection of chemical compounds using binary strings. Technometrics 2002, 44, 110-119.
19. Baroni-Urbani, C.; Buser, M. W. Similarity ofbinary data. Syst. Zool. 1976, 25, 251-159.
20. Symyx Technologies. MDL Drug Data Report. http://mdli.com/products/ knowledge/drug-data-report (accessed 10 Nov 2008).
21. Molconn-Z, version 4.0; eduSoft, LC: Ashland, VA, 2006.
22. Hert, J.; Willett, P.; Wilton, D. J.; Acklin, P.; Azzaoui, K.; Jacoby, E.; Schuffenhauer, A. Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures. J. Chem. Inf. Comput. Sci. 2004, 44, 1177-1185.
23. Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Delivery Rev. 1997, 23, 3-25.