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A Primer on Molecular Similarity in QSAR and Virtual Screening
Part III - Model Generation

References

1. Todeschini, R.; Consonni, V., Handbook of Molecular Descriptors. Wiley-VCH: Weinheim, 2000.

2. Topliss, J. G.; Edwards, R. P., Chance factors in studies of quantitative structure-activity relationships. J. Med. Chem. 1979, 22, (10), 1238-44.

3. Livingstone, D. J.; Manallack, D. T.; Tetko, I. V., Data modelling with neural networks: Advantages and limitations. J. Comput.-Aided Mol. Des. 1997, 11, (2), 135-142.

4. Livingstone, D. J.; Salt, D. W., Judging the significance of multiple linear regression models. J. Med. Chem. 2005, 48, (3), 661-3.

5. Golbraikh, A.; Tropsha, A., Beware of q2! J. Mol. Graph. Model. 2002, 20, (4), 269-76.

6. Hawkins, D. M.; Basak, S. C.; Mills, D., Assessing model fit by cross-validation. J. Chem. Inf. Comput. Sci. 2003, 43, (2), 579-86.

7. Baumann, K.; Albert, H.; von Korff, M., A systematic evaluation of the benefits and hazards of variable selection in latent variable regression. Part I. Search algorithm, theory and simulations. J. Chemometr. 2002, 16, (7), 339-350.

8. Baumann, K.; von Korff, M.; Albert, H., A systematic evaluation of the benefits and hazards of variable selection in latent variable regression. Part II. Practical applications. J. Chemometr. 2002, 16, (7), 351-360.

9. Papa, E.; Villa, F.; Gramatica, P., Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow). J. Chem Inf. Model. 2005, 45, (5), 1256-1266.

10. Dimitrov, S.; Dimitrova, G.; Pavlov, T.; Dimitrova, N.; Patlewicz, G.; Niemela, J.; Mekenyan, O., A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models. J. Chem. Inf. Model. 2005, 45, (4), 839 - 849.

11. Guha, R.; Jurs, P. C., Determining the validity of a QSAR model - A classification approach. J. Chem. Inf. Model. 2005, 45, (1), 65-73.

12. Walker, J. D.; Carlsen, L.; Jaworska, J., Improving opportunities for regulatory acceptance of QSARs: The importance of model domain, uncertainty, validity and predictability. QSAR Comb. Sci. 2003, 22, (3), 346-350.

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