230
T. Hanser et al.
References
1. OECD (2007) Guidance document on the validation of (quantitative) structure-activity relationship [(Q)SAR] models. In: OECD series on testing and assessment, No. 69. OECD Publishing,
Paris. https://doi.org/10.1787/9789264085442-en. Accessed 10 Sept 2018
2. Mathea M et al (2016) Chemoinformatic classification methods and their applicability domain.
Mol Inf 35(5):160–180
3. Eriksson L et al (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect
111(10):1361–1375
4. Carrió P et al (2014) Applicability domain analysis (ADAN): a robust method for assessing
the reliability of drug property predictions. J Chem Inf Model 54(5):1500–1511
5. Netzeva TI et al (2005) Current status of methods for defining the applicability domain of
(quantitative) structure—activity relationships. Altern Lab Anim 32(2):155–173
6. Dragos H et al (2009) Predicting the predictability: a unified approach to the applicability
domain problem of QSAR models. J Chem Inf Model 49(7):1762–1776
7. Sahigara F et al (2012) Comparison of different approaches to define the applicability domain
of QSAR models. Molecules 17(5):4791–4810
8. Ochi S et al (2017) Structure modification toward applicability domain of a QSAR/QSPR
model considering activity/property. Mol Inf 36(12):1700076
9. Sheridan RP (2012) Three useful dimensions for domain applicability in QSAR models using
random forest. J Chem Inf Model 52(3):814–823
10. Sahigara F et al (2013) Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions. J Cheminform 5(1):27
11. Sheridan RP et al (2004) Similarity to molecules in the training set is a good discriminator for
prediction accuracy in QSAR. J Chem Inf Comput Sci 44(6):1912–1928
12. Toplak M et al (2014) Assessment of machine learning reliability methods for quantifying the
applicability domain of QSAR regression models. J Chem Inf Model 54(2):431–441
13. Sheridan RP (2015) The relative importance of domain applicability metrics for estimating
prediction errors in QSAR varies with training set diversity. J Chem Inf Model 55(6):1098–1107
14. Roy K et al (2015) On a simple approach for determining applicability domain of QSAR
models. Chemom Intell Lab Syst 145:22–29
15. Gadaleta D (2016) Applicability domain for QSAR models: where theory meets reality. Intern
J Quant Struct Prop Relat 1(1):45–63
16. Hanser T (2016) Applicability domain: towards a more formal definition. SAR QSAR Environ
Res 27(11):893–909
17. Wikipedia https://en.wikipedia.org/wiki/Curse_of_dimensionality. Accessed 10 Sept 2018
18. Nikolova-Jeliazkova N, Jaworska J (2005) An approach to determining applicability domains
for QSAR group contribution models: an analysis of SRC KOWWIN. Altern Lab Anim
33(5):461–470
19. Rogers D, Hahn M (2010) Extended-connectivity fingerprints. J Chem Inf Model
50(5):742–754
20. MACCS structural keys (2011) Accelrys, San Diego, CA
21. Carhart RE et al (1985) Atom pairs as molecular features in structure-activity studies: definition
and applications. J Chem Inf Comput Sci 25(2):64–73
22. Gobbi A, Poppinger D (1998) Genetic optimization of combinatorial libraries. Biotech Bioeng
61(1):47–54
23. Nilakantan R et al (1987) Topological torsion: a new molecular descriptor for SAR applications.
Comparison with other descriptors. J Chem Inf Comput Sci 27(2):82–85
24. Dimitrov S et al (2005) A stepwise approach for defining the applicability domain of SAR and
QSAR models. J Chem Inf Model 45(4):839–849
25. Willett P et al (1998) Chemical similarity searching. J Chem Inf Comput Sci 38(6):983–996
T. Hanser et al.
References
1. OECD (2007) Guidance document on the validation of (quantitative) structure-activity relationship [(Q)SAR] models. In: OECD series on testing and assessment, No. 69. OECD Publishing,
Paris. https://doi.org/10.1787/9789264085442-en. Accessed 10 Sept 2018
2. Mathea M et al (2016) Chemoinformatic classification methods and their applicability domain.
Mol Inf 35(5):160–180
3. Eriksson L et al (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect
111(10):1361–1375
4. Carrió P et al (2014) Applicability domain analysis (ADAN): a robust method for assessing
the reliability of drug property predictions. J Chem Inf Model 54(5):1500–1511
5. Netzeva TI et al (2005) Current status of methods for defining the applicability domain of
(quantitative) structure—activity relationships. Altern Lab Anim 32(2):155–173
6. Dragos H et al (2009) Predicting the predictability: a unified approach to the applicability
domain problem of QSAR models. J Chem Inf Model 49(7):1762–1776
7. Sahigara F et al (2012) Comparison of different approaches to define the applicability domain
of QSAR models. Molecules 17(5):4791–4810
8. Ochi S et al (2017) Structure modification toward applicability domain of a QSAR/QSPR
model considering activity/property. Mol Inf 36(12):1700076
9. Sheridan RP (2012) Three useful dimensions for domain applicability in QSAR models using
random forest. J Chem Inf Model 52(3):814–823
10. Sahigara F et al (2013) Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions. J Cheminform 5(1):27
11. Sheridan RP et al (2004) Similarity to molecules in the training set is a good discriminator for
prediction accuracy in QSAR. J Chem Inf Comput Sci 44(6):1912–1928
12. Toplak M et al (2014) Assessment of machine learning reliability methods for quantifying the
applicability domain of QSAR regression models. J Chem Inf Model 54(2):431–441
13. Sheridan RP (2015) The relative importance of domain applicability metrics for estimating
prediction errors in QSAR varies with training set diversity. J Chem Inf Model 55(6):1098–1107
14. Roy K et al (2015) On a simple approach for determining applicability domain of QSAR
models. Chemom Intell Lab Syst 145:22–29
15. Gadaleta D (2016) Applicability domain for QSAR models: where theory meets reality. Intern
J Quant Struct Prop Relat 1(1):45–63
16. Hanser T (2016) Applicability domain: towards a more formal definition. SAR QSAR Environ
Res 27(11):893–909
17. Wikipedia https://en.wikipedia.org/wiki/Curse_of_dimensionality. Accessed 10 Sept 2018
18. Nikolova-Jeliazkova N, Jaworska J (2005) An approach to determining applicability domains
for QSAR group contribution models: an analysis of SRC KOWWIN. Altern Lab Anim
33(5):461–470
19. Rogers D, Hahn M (2010) Extended-connectivity fingerprints. J Chem Inf Model
50(5):742–754
20. MACCS structural keys (2011) Accelrys, San Diego, CA
21. Carhart RE et al (1985) Atom pairs as molecular features in structure-activity studies: definition
and applications. J Chem Inf Comput Sci 25(2):64–73
22. Gobbi A, Poppinger D (1998) Genetic optimization of combinatorial libraries. Biotech Bioeng
61(1):47–54
23. Nilakantan R et al (1987) Topological torsion: a new molecular descriptor for SAR applications.
Comparison with other descriptors. J Chem Inf Comput Sci 27(2):82–85
24. Dimitrov S et al (2005) A stepwise approach for defining the applicability domain of SAR and
QSAR models. J Chem Inf Model 45(4):839–849
25. Willett P et al (1998) Chemical similarity searching. J Chem Inf Comput Sci 38(6):983–996