Registro:

Referencias:

• Matthews, G., (2015) Pesticides: Health, Safety and the Environment, , 2nd ed., Wiley-Blackwell, New York
• Nowell, L.H., Capel, P.D., Dileanis, P.D., (1999) Pesticides in Stream Sediment and Aquatic Biota: Distribution, Trends, and Governing Factors, , CRC Press, Boca Ratón, FL:, and
• Matthews, G., Bateman, R., Miller, P., (2014) Pesticide Application Methods, , 4th ed., Wiley-Blackwell, New York:, and
• Beek, B., (2013) Bioaccumulation New Aspects and Developments, , The Handbook of Environmental Chemistry, Springer, Berlin
• Grisoni, F., Consonni, V., Villa, S., Vighi, M., Todeschini, T., QSAR models for bioconcentration: Is the increase in the complexity justified by more accurate predictions? (2015) Chemosphere, 127, pp. 171-179
• Hansch, C., Leo, A., (1995) Exploring QSAR. Fundamentals and Applications in Chemistry and Biology, , American Chemical Society, Washington, DC: and
• Benfenati, E., (2013) Theory, guidance and applications on QSAR and REACH, , https://ebook.insilico.eu/insilico-ebook-orchestra-benfenati-ed1_rev-June2013.pdf, Orchestra
• Roy, K., Kar, S., Narayan Das, R., (2015) Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment, , Academic Press, New York:, and
• Benfenati, E., (2007) Quantitative Structure-Activity Relationships (QSAR) for Pesticide Regulatory Purposes, , Elsevier Science, Amsterdam
• Knaak, J.P., Timchalk, C., Tornero-Velez, R., (2013) Parameters for pesticide QSAR and PBPK/PD models for human risk assessment, , Oxford University Press, Oxford:, and
• Katritzky, A.R., Goordeva, E.V., Traditional topological indices vs. electronic, geometrical, and combined molecular descriptors in QSAR/QSPR research (1993) J. Chem. Inf. Comput. Sci., 33, pp. 835-857
• Diudea, M.V.E., (2001) QSPR/QSAR Studies by Molecular Descriptors, , Nova Science Publishers, New York
• Todeschini, R., Consonni, V., (2009) Molecular Descriptors for Chemoinformatics, Methods and Principles in Medicinal Chemistry, , Wiley-VCH, Weinheim: and
• Pavan, M., Worth, A.P., Netzeva, T.I., (2006) Review of QSAR Models for Bioconcentration, , JRC report EUR EN I-21020, and
• Lombardo, A., Roncaglioni, A., Boriani, E., Milan, C., Benfenati, E., Assessment and validation of the CAESAR predictive model for bioconcentration factor (BCF) in fish (2010) Chem. Cent. J., 4, p. S1
• Zhao, C., Boriani, E., Chana, A., Roncaglioni, A., Benfenati, E., A new hybrid system of QSAR models for predicting bioconcentration factors (BCF) (2008) Chemosphere, 73, pp. 1701-1707
• (2017), https://www.vega-qsar.eu/; Meylan, W., Howard, P., Boethling, R., Aronson, D., Printup, H., Gouchie, S., Improved method for estimating bioconcentration/bioaccumulation factor from octanol/water partition coefficient (1999) Environ. Toxicol. Chem., 18, pp. 664-672
• (2017) U.S.EPA, , https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-interface
• (2017), https://www.epa.gov/nrmrl/std/qsar/qsar.html; Gissi, A., Gadaleta, D., Floris, M., Olla, S., Carotti, A., Novelllino, E., Benfenati, E., Nicolotti, O., An alternative QSAR-based approach for predicting the bioconcentration factor for regulatory purposes (2014) ALTEX, 31, pp. 23-26
• Gissi, A., Nicolotti, O., Carotti, A., Gadaleta, D., Lombardo, A., Benfenati, E., Integration of QSAR models for bioconcentration suitable for REACH (2013) Sci. Total Environ., 456-457, pp. 325-332
• Duchowicz, P.R., Comelli, N.C., Ortiz, E.V., Castro, E.A., QSAR study for carcinogenicity in a large set of organic compounds (2012) Curr. Drug Saf., 7, pp. 282-288
• Duchowicz, P.R., Bennardi, D.O., Baselo, D.E., Bonifazi, E.L., Rios-Luci, C., Padrón, J.M., Burton, G., Misico, R.I., QSAR on antiproliferative naphthoquinones based on a conformation-independent approach (2014) Eur. J. Med. Chem., 77, pp. 176-184
• Duchowicz, P.R., Fioressi, S.E., Bacelo, D.E., Saavedra, L.M., Toropova, A.P., Toropov, A.A., QSPR studies on refractive indices of structurally heterogeneous polymers (2015) Chemom. Intel. Lab. Syst., 140, pp. 86-91
• Aranda, J.F., Garro Martinez, J.C., Castro, E.A., Duchowicz, P.R., Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds (2016) Int. J. Mol. Sci., 17, p. 1247
• (2017), http://www.acdlabs.com; (2017), https://openbabel.org/wiki/Category:Installation; (2017), https://www.yapcwsoft.com/; Yap, C.W., PaDEL-Descriptor: An open source software to calculate molecular descriptors and fingerprints (2011) J. Comput. Chem., 32, pp. 1466-1474
• Toropov, A.A., Toropova, A.P., Benfenati, E., Gini, G., Puzyn, T., Leszczynska, D., Leszczynski, J., Novel application of the coral software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (2012) Chemosphere, 89, pp. 1098-1102
• Toropova, A.P., Toropov, A.A., Martyanov, S.E., Benfenati, E., Gini, G., Leszczynska, D., Leszczynski, J., Coral: QSAR modeling of toxicity of organic chemicals towards Daphnia magna (2012) Chemom. Intel. Lab. Syst., 110, pp. 177-181
• Fioressi, S.E., Bacelo, D.E., Cui, W.P., Saavedra, L.M., Duchowicz, P.R., QSPR study on refractive indices of solvents commonly used in polymer chemistry using flexible molecular descriptors (2015) SAR QSAR Environ. Res., 26, pp. 499-506
• (2017) Coral 1.5, , https://www.insilico.eu/coral
• Hong, H., Xie, Q., Ge, W., Qian, F., Fang, H., Shi, L., Su, Z., Tong, W., Mold2, molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics (2008) J. Chem. Inf. Model., 48, pp. 1337-1344
• (2017), https://reccr.chem.rpi.edu/Software/RECON/recondoc/ReconManual.html; Lavine, B.K., Davidson, C.E., Breneman, C., Katt, W., Electronic van der Waals surface property descriptors and genetic algorithms for developing structure-activity correlations in olfactory databases (2003) J. Chem. Inf. Comput. Sci., 43, pp. 1890-1905
• Bader, R.F.W., (1990) Atoms in Molecules-A Quantum Theory, , Oxford University Press, Oxford, UK
• Breneman, C.M., Rhem, M., A QSPR analysis of HPLC column capacity factors for a set of high-energy materials using electronic Van der Waals surface property descriptors computed by the transferable atom equivalent method (1997) J. Comput. Chem., 18, pp. 182-197
• Valdes-Martini, J.R., García Jacas, C.R., Marrero-Ponce, Y., Silveira Vaz ‘d Almeida, Y., Morrel, C., (2012) QuBiLS-MAS: Free Software for molecular descriptors calculator from Quadratic, Bilinear and Linear Maps based on Graph–Theoretic Electronic-Density Matrices and Atomic weighting, , Version 1.0. CAMD-BIR Unit, CENDA Number of register: 2373-2012, and
• Duchowicz, P.R., Castro, E.A., Fernández, F.M., Alternative algorithm for the search of an optimal set of descriptors in QSAR-QSPR Studies (2006) MATCH Commun. Math. Comput. Chem., 55, pp. 179-192
• Morales, A.H., Duchowicz, P.R., Cabrera Pérez, M.A., Castro, E.A., Cordeiro, M.N.D.S., González, M.P., Application of the replacement method as a novel variable selection strategy in QSAR. 1. Carcinogenic potential (2006) Chemom. Intel. Lab. Syst., 81, pp. 180-187
• (2017) The MathWorks, Inc, , https://www.mathworks.com
• Gramatica, P., Sangion, A., A historical excursus on the statistical validation parameters for QSAR models: A clarification concerning metrics and terminology (2016) J. Chem. Inf. Model., 56, pp. 1127-1131
• Roy, K., Das, R.N., Ambure, P., Aher, R.B., Be aware of error measures. Further studies on validation of predictive QSAR models (2016) Chemom. Intel. Lab. Syst, 152, pp. 18-33
• Rojas, C., Duchowicz, P.R., Tripaldi, P., Pis Diez, R., Quantitative structure-property relationship analysis for the retention index of fragrance-like compounds on a polar stationary phase (2015) J. Chromatogr. A, 1422, pp. 277-288
• Duchowicz, P.R., Fioressi, S.E., Castro, E.A., Wróbel, K., Ibezim, N.E., Bacelo, D.E., Conformation-independent QSAR study on human epidermal growth factor receptor-2 (HER2) inhibitors (2017) Chem. Select., 2, pp. 3725-3731
• Kaufman, L., Rousseeuw, P.J., (2005) Finding Groups in Data: An Introduction to Cluster Analysis, , Wiley, New York: and
• Golbraikh, A., Tropsha, A., Beware of q2! (2002) J. Mol. Graphics Modell., 20, pp. 269-276
• Rücker, C., Rücker, G., Meringer, M., Y-Randomization and its variants in QSPR/QSAR (2007) J. Chem. Inf. Model., 47, pp. 2345-2357
• Gramatica, P., Principles of QSAR models validation: Internal and external (2007) QSAR Comb. Sci., 26, pp. 694-701
• Roy, K., Kar, S., Ambure, P., On a simple approach for determining applicability domain of QSAR models (2015) Chemom. Intel. Lab. Syst., 145, pp. 22-29
• Eriksson, L., Jaworska, J., Worth, A.P., Cronin, M.T., McDowell, R.M., Gramatica, P., Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs (2003) Environ. Health Perspect., 111, pp. 1361-1375
• Draper, N.R., Smith, H., (1981) Applied Regression Analysis, , John Wiley & Sons, New York: and
• Roy, K., Roy, P.P., Comparative chemometric modeling of cytochrome 3A4 inhibitory activity of structurally diverse compounds using stepwise MLR, FAMLR, PLS, GFA, G/PLS and ANN techniques (2009) Eur. J. Med. Chem., 44, pp. 2913-2922

Citas:

---------- APA ----------

---------- CHICAGO ----------

---------- MLA ----------

---------- VANCOUVER ----------