401
Views
15
CrossRef citations to date
0
Altmetric
Articles

Classification of biodegradable materials using QSAR modelling with uncertainty estimationFootnote§

&
Pages 799-811 | Received 17 Jun 2016, Accepted 13 Sep 2016, Published online: 06 Oct 2016

References

  • A.V. Colling, L.B. Oliveira, M.M. Reis, N.T. da Cruz, and J.D. Hunt, Brazilian recycling potential: Energy consumption and green house gases reduction, Renew. Sust. Energ. Rev. 59 (2016), pp. 544–549.
  • D. Allinson, K.N. Irvine, J.L. Edmondson, A. Tiwary, G. Hill, J. Morris, M. Bell, Z.G. Davies, S.K. Firth, J. Fisher, K.J. Gaston, J.R. Leake, N. McHugh, A. Namdeo, M. Rylatt, and K. Lomas, Measurement and analysis of household carbon: The case of a UK city, Appl. Energy 164 (2016), pp. 871–881.
  • G. Lazzerini, S. Lucchetti, and F.P. Nicese, Green house gases (GHG) emissions from the ornamental plant nursery industry: A Life Cycle Assessment (LCA) approach in a nursery district in central Italy, J. Clean Prod. 112 (2016), pp. 4022–4030.
  • A.D. Adam and G. Apaydin, Grid connected solar photovoltaic system as a tool for green house gas emission reduction in Turkey, Renew. Sust. Energ. Rev. 53 (2016), pp. 1086–1091.
  • S.W. Goh, J.S. Zhang, Y. Liu, and A.G. Fane, Membrane distillation bioreactor (MDBR) – A lower green-house-gas (GHG) option for industrial wastewater reclamation, Chemosphere 140 (2015), pp. 129–142.
  • L.H. Meng, C.C. Gao, L. Yu, G.P. Simon, H.S. Liu, and L. Chen, Biodegradable composites of poly(butylene succinate-co-butylene adipate) reinforced by poly(lactic acid) fibers, J. Appl. Polym. Sci. 133 (2016), p. 6.
  • R.G. Wang, T.G. Ren, Y.X. Bai, Y.Z. Wang, J.F. Chen, L.Q. Zhang, and X.Y. Zhao, One-pot synthesis of biodegradable and linear poly(ester amide)s based on renewable resources, J. Appl. Polym. Sci. 133 (2016), p. 6.
  • X.Y. Peng, Y.X. Zhang, Y. Chen, S. Li, and B. He, Synthesis and crystallization of well-defined biodegradable miktoarm star PEG-PCL-PLLA copolymer, Mater. Lett. 171 (2016), pp. 83–86.
  • F.C. Ma, S. Chen, P. Liu, F. Geng, W. Li, X.K. Liu, D.H. He, and D. Pan, Improvement of beta-TCP/PLLA biodegradable material by surface modification with stearic acid, Mater. Sci. Eng. C-Mater. Biol. Appl. 62 (2016), pp. 407–413.
  • Y.H. Wu, X.G. Luo, W. Li, R. Song, J. Li, Y. Li, B. Li, and S.L. Liu, Green and biodegradable composite films with novel antimicrobial performance based on cellulose, Food Chem. 197 (2016), pp. 250–256.
  • P.K. Qi, Y. Yang, S. Zhao, J. Wang, X.Y. Li, Q.F. Tu, Z.L. Yang, and N. Huang, Improvement of corrosion resistance and biocompatibility of biodegradable metallic vascular stent via plasma allylamine polymerized coating, Mater. Des. 96 (2016), pp. 341–349.
  • S. Soltani, U. Rashid, R. Yunus, and Y.H. Taufiq-Yap, Biodiesel production in the presence of sulfonated mesoporous ZnAl2O4 catalyst via esterification of palm fatty acid distillate (PFAD), Fuel 178 (2016), pp. 253–262.
  • J. Ahmad, S. Yusup, A. Bokhari, and R.N.M. Kamil, Biodiesel production from the high free fatty acid “Hevea brasiliensis” and fuel properties characterization, in Process and Advanced Materials Engineering, I. Ahmed, ed., Trans Tech Publications Ltd, Stafa-Zurich, 2014, pp. 897–900.
  • S. Chattopadhyay and R. Sen, Fuel properties, engine performance and environmental benefits of biodiesel produced by a green process, Appl. Energy 105 (2013), pp. 319–326.
  • L.V. Rasmussen, K. Rasmussen, and T.B. Bruun, Impacts of Jatropha-based biodiesel production on above and below-ground carbon stocks: A case study from Mozambique, Energ. Policy 51 (2012), pp. 728–736.
  • A. Fernandez, R. Rallo, and F. Giralt, Prioritization of in silico models and molecular descriptors for the assessment of ready biodegradability, Environ. Res. 142 (2015), pp. 161–168.
  • L. Ceriani, E. Papa, S. Kovarich, R. Boethling, and P. Gramatica, Modeling ready biodegradability of fragrance materials, Environ. Toxicol. Chem. 34 (2015), pp. 1224–1231.
  • P. Xu, W.C. Ma, H.J. Han, S.Y. Jia, and B.L. Hou, Quantitative structure-biodegradability relationships for biokinetic parameter of polycyclic aromatic hydrocarbons, J. Environ. Sci. 30 (2015), pp. 180–185.
  • R. Boethling, Comparison of ready biodegradation estimation methods for fragrance materials, Sci. Total Environ. 497 (2014), pp. 60–67.
  • A. Lombardo, F. Pizzo, E. Benfenati, A. Manganaro, T. Ferrari, and G. Gini, A new in silico classification model for ready biodegradability, based on molecular fragments, Chemosphere 108 (2014), pp. 10–16.
  • A. Sabljic and Y. Nakagawa, Biodegradation and quantitative structure–activity relationship (QSAR), in Non-First Order Degradation and Time-Dependent Sorption of Organic Chemicals in Soil, W.L. Chen, A. Sabljic, S.A. Cryer, and R.S. Kookana, eds., American Chemical Society, Washington, 2014, pp. 57–84.
  • S. Vorberg and I.V. Tetko, Modeling the biodegradability of chemical compounds using the Online CHEmical Modeling Environment (OCHEM), Mol. Inf. 33 (2014), pp. 73–85.
  • M.P. Gonzalez, C. Teran, L. Saiz-Urra, and M. Teijeira, Variable selection methods in QSAR: An overview, Curr. Topics Med. Chem. 8 (2008), pp. 1606–1627.
  • A. Yasri and D. Hartsough, Toward an optimal procedure for variable selection and QSAR model building, J. Chem. Inf. Model. 41 (2001), pp. 1218–1227.
  • S. Gupta and J. Aires-De-Sousa, Comparing the chemical spaces of metabolites and available chemicals: Models of metabolite-likeness, Mol. Divers. 11 (2007), pp. 23–36.
  • T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second ed., Springer-Verlag, 2009.
  • W. Bich, Error, uncertainty and probability, in Metrology and Physical Constants, E. Bava, M. Kuhne, and A.M. Rossi, eds., 2013, pp. 47–73.
  • W. Bich, Revision of the ‘Guide to the Expression of Uncertainty in Measurement’, Why and how, Metrologia 51 (2014), pp. S155–S158.
  • W. Bich, M.G. Cox, R. Dybkaer, C. Elster, W.T. Estler, B. Hibbert, H. Imai, W. Kool, C. Michotte, L. Nielsen, L. Pendrill, S. Sidney, A.M.H. van der Veen, and W. Woger, Revision of the ‘Guide to the Expression of Uncertainty in Measurement’, Metrologia 49 (2012), pp. 702–705.
  • W. Bich, M.G. Cox, and P.M. Harris, Evolution of the ‘Guide to the Expression of Uncertainty in Measurement’, Metrologia 43 (2006), pp. S161–S166.
  • K. Mansouri, T. Ringsted, D. Ballabio, R. Todeschini, and V. Consonni, Quantitative structure–activity relationship models for ready biodegradability of chemicals, J. Chem. Inf. Model. 53 (2013), pp. 867–878.
  • D. Ballabio and V. Consonni, Classification tools in chemistry. Part 1: Linear models. PLS-DA, Anal. Method. 5 (2013), pp. 3790–3798.
  • M.R. de Almeida, D.N. Correa, W.F.C. Rocha, F.J.O. Scafi, and R.J. Poppi, Discrimination between authentic and counterfeit banknotes using Raman spectroscopy and PLS-DA with uncertainty estimation, Microchem. J. 109 (2013), pp. 170–177.
  • B. Worley, S. Halouska, and R. Powers, Utilities for quantifying separation in PCA/PLS-DA scores plots, Anal. Biochem. 433 (2013), pp. 102–104.
  • J. Xia and D.S. Wishart, Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst, Nat. Protoc. 6 (2011), pp. 743–760.
  • F.B. Gonzaga, W.F.d.C. Rocha, and D.N. Correa, Discrimination between authentic and false tax stamps from liquor bottles using laser-induced breakdown spectroscopy and chemometrics, Spectrochim. Acta B 109 (2015), pp. 24–30.
  • A.S. Luna, I.C.A. Lima, W.F.C. Rocha, J.R. Araujo, A. Kuznetsov, E.H.M. Ferreira, R. Boque, and J. Ferre, Classification of soil samples based on Raman spectroscopy and X-ray fluorescence spectrometry combined with chemometric methods and variable selection, Anal. Method. 6 (2014), pp. 8930–8939.
  • H. Chun and S. Keleş, Sparse partial least squares regression for simultaneous dimension reduction and variable selection, J. Royal Stat. Soc. Ser. B (Stat. Methodol.) 72 (2010), pp. 3–25.
  • S. Wold, M. Sjöström, and L. Eriksson, PLS-regression: A basic tool of chemometrics, Chemometr. Intell. Lab. 58 (2001), pp. 109–130.
  • PLS Toolbox 4.0. Eigenvector Research, Inc., Manson, WA, 2006.
  • M.X. Rodriguez-Alvarez, L. Meira-Machado, E. Abu-Assi, and S. Raposeiras-Roubin, Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate, Stat. Med. 35 (2016), pp. 1090–1102.
  • W. Aziz, M. Rafique, I. Ahmad, M. Arif, N. Habib, and M.S.A. Nadeem, Classification of heart rate signals of healthy and pathological subjects using threshold based symbolic entropy, Acta Biol. Hung. 65 (2014), pp. 252–264.
  • M. Leila and S. van de Geer, On threshold-based classification rules, Lect. Notes-Monogr. Ser. 42 (2003), pp. 261–280.
  • R. Beran, Refining bootstrap simultaneous confidence sets, J. Am. Stat. Assoc. 85 (1990), pp. 417–426.
  • D. Burr, A comparison of certain bootstrap confidence intervals in the Cox model, J. Am. Stat. Assoc. 89 (1994), pp. 1290–1302.
  • H. van der Voet, Pseudo-degrees of freedom for complex predictive models: The example of partial least squares, J. Chemom. 13 (1999), pp. 195–208.
  • R. Wehrens, H. Putter, and L.M.C. Buydens, The bootstrap: A tutorial, Chemom. Intell. Lab. 54 (2000), pp. 35–52.
  • R.S. Boethling, Designing biodegradable chemicals, in Designing Safer Chemicals, Vol. 640, S.C. DeVito and R.L. Garrett, eds., American Chemical Society, Washington, DC, 1996, pp. 156–171.
  • S.C. DeVito and R.L. Garrett, Designing Safer Chemicals, Vol. 640, ACS Symposium Series, American Chemical Society, Washington, DC, 1996.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.