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Linked References

1. M. A. Johnson and G. M. Maggiora, Concepts and Application of Molecular Similarity, John Wiley & Sons, New York, NY, USA, 1990.
2. P. Willett, J. M. Barnard, and G. M. Downs, “Chemical similarity searching,” Journal of Chemical Information and Computer Sciences, vol. 38, no. 6, pp. 983–996, 1998. View at Google Scholar · View at Scopus
3. W. P. Walters, M. T. Stahl, and M. A. Murcko, “Virtual screening—an overview,” Drug Discovery Today, vol. 3, no. 4, pp. 160–178, 1998. View at Google Scholar · View at Scopus
4. B. Waszkowycz, T. D. J. Perkins, R. A. Sykes, and J. Li, “Large-scale virtual screening for discovering leads in the postgenomic era,” IBM Systems Journal, vol. 40, no. 2, pp. 360–378, 2001. View at Google Scholar · View at Scopus
5. M. A. Miller, “Chemical database techniques in drug discovery,” Nature Reviews Drug Discovery, vol. 1, no. 3, pp. 220–227, 2002. View at Google Scholar · View at Scopus
6. H. Eckert and J. Bajorath, “Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches,” Drug Discovery Today, vol. 12, no. 5-6, pp. 225–233, 2007. View at Publisher · View at Google Scholar · View at Scopus
7. R. P. Sheridan, “Chemical similarity searches: when is complexity justified?” Expert Opinion on Drug Discovery, vol. 2, no. 4, pp. 423–430, 2007. View at Publisher · View at Google Scholar · View at Scopus
8. H. Geppert, M. Vogt, and J. Bajorath, “Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluation,” Journal of Chemical Information and Modeling, vol. 50, no. 2, pp. 205–216, 2010. View at Publisher · View at Google Scholar · View at Scopus
9. R. P. Sheridan and S. K. Kearsley, “Why do we need so many chemical similarity search methods?” Drug Discovery Today, vol. 7, no. 17, pp. 903–911, 2002. View at Publisher · View at Google Scholar · View at Scopus
10. N. Nikolova and J. Jaworska, “Approaches to measure chemical similarity—a Review,” QSAR & Combinatorial Science, vol. 22, no. 9-10, pp. 1006–1026, 2003. View at Google Scholar
11. A. Bender and R. C. Glen, “Molecular similarity: a key technique in molecular informatics,” Organic and Biomolecular Chemistry, vol. 2, no. 22, pp. 3204–3218, 2004. View at Publisher · View at Google Scholar · View at Scopus
12. A. G. Maldonado, J. P. Doucet, M. Petitjean, and B. T. Fan, “Molecular similarity and diversity in chemoinformatics: from theory to applications,” Molecular Diversity, vol. 10, no. 1, pp. 39–79, 2006. View at Publisher · View at Google Scholar · View at Scopus
13. A. R. Leach and V. J. Gillet, An Introduction to Chemoinformatics, Springer, 2007.
14. P. Willett, “Enhancing the effectiveness of ligand-based virtual screening using data fusion,” QSAR & Combinatorial Science, vol. 25, no. 12, pp. 1143–1152, 2006. View at Publisher · View at Google Scholar · View at Scopus
15. L. Hodes, “Clustering a large number of compounds. 1. Establishing the method on an initial sample,” Journal of Chemical Information and Computer Sciences, vol. 29, pp. 66–71, 1989. View at Google Scholar · View at Scopus
16. P. Willett and V. Winterman, “A comparison of some measures for the determination of inter-molecular structural similarity measures of inter-molecular structural similarity,” Quantitative Structure-Activity Relationships, vol. 5, no. 1, pp. 18–25, 1986. View at Google Scholar · View at Scopus
17. P. A. Bath, C. A. Morris, and P. Willett, “Effect of standardization on fragment‐based measures of structural similarity,” Journal of chemometrics, vol. 7, pp. 543–550, 1993. View at Google Scholar
18. J. D. Holliday, C. Y. Hu, and P. Willett, “Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings,” Combinatorial Chemistry & High Throughput Screening, vol. 5, no. 2, pp. 155–166, 2002. View at Google Scholar · View at Scopus
19. H. Turtle and W. B. Croft, “Evaluation of an inference network-based retrieval model,” ACM Transactions on Information Systems, vol. 9, pp. 187–222, 1991. View at Google Scholar
20. D. Haines and W. B. Croft, “Relevance feedback and inference networks,” in Proceedings of the 16th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '93), pp. 2–11, July 1993. View at Scopus
21. L. M. De Campos, J. M. Fernández-Luna, and J. F. Huete, “Implementing relevance feedback in the Bayesian network retrieval model,” Journal of the American Society for Information Science & Technology, vol. 54, no. 4, pp. 302–313, 2003. View at Publisher · View at Google Scholar · View at Scopus
22. J. Xin and J. S. Jin, “Relevance feedback for content-based image retrieval using Bayesian network,” in Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing (VIP '05), pp. 91–94, 2004.
23. A. Abdo, N. Salim, and A. Ahmed, “Implementing relevance feedback in ligand-based virtual screening using bayesian inference network,” Journal of Biomolecular Screening, vol. 16, no. 9, pp. 1081–1088, 2011. View at Publisher · View at Google Scholar
24. A. Abdo and N. Salim, “New fragment weighting scheme for the Bayesian inference network in ligand-based virtual screening,” Journal of Chemical Information and Modeling, vol. 51, no. 1, pp. 25–32, 2011. View at Publisher · View at Google Scholar
25. D. Ellis, J. F. Hines, and P. Willett, “Measuring the degree of similarity between objects in text retrieval systems,” Perspectives in Information Management, vol. 3, pp. 128–149, 1993. View at Google Scholar
26. A. Abdo and N. Salim, “Similarity-based virtual screening with a bayesian inference network,” ChemMedChem, vol. 4, no. 2, pp. 210–218, 2009. View at Publisher · View at Google Scholar · View at Scopus
27. B. Chen, C. Mueller, and P. Willett, “Evaluation of a Bayesian inference network for ligand-based virtual screening,” Journal of Cheminformatics, vol. 1, article 5, 2009. View at Google Scholar
28. Pipeline Pilot, Accelrys Software, San Diego, Calif, USA, 2008.
29. J. Hert, P. Willett, D. J. Wilton et al., “New methods for ligand-based virtual screening: use of data fusion and machine learning to enhance the effectiveness of similarity searching,” Journal of Chemical Information and Modeling, vol. 46, no. 2, pp. 462–470, 2006. View at Publisher · View at Google Scholar · View at Scopus
30. S. Siegel and N. J. Castellan, Nonparametric Statistics for the Behavioral Sciences, McGraw-Hill, 1988.