구조-활성의 정량적 관계 (Korean Wikipedia)

Analysis of information sources in references of the Wikipedia article "구조-활성의 정량적 관계" in Korean language version.

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27doi.org

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14nih.gov

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9archive.org

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3harvard.edu

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1worldcat.org

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1jcheminf.com

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archive.org

《Molecular modelling: principles and applications》. Englewood Cliffs, N.J: Prentice Hall. 2001. ISBN 0-582-38210-6.
《Kernel methods in computational biology》. Cambridge, Mass: MIT Press. 2004. ISBN 0-262-19509-7.
《Algorithms on strings, trees, and sequences: computer science and computational biology》. Cambridge, UK: Cambridge University Press. 1997. ISBN 0-521-58519-8.
《Predictive toxicology》. Washington, DC: Taylor & Francis. 2005. ISBN 0-8247-2397-X.
Waterbeemd, Han van de, 편집. (1995). 〈Statistical validation of QSAR results〉. 《Chemometric methods in molecular design》. Weinheim: VCH. 309–318쪽. ISBN 3-527-30044-9.
《Chemical graph theory: introduction and fundamentals》. Tunbridge Wells, Kent, England: Abacus Press. 1991. ISBN 0-85626-454-7.
“Structural modeling extends QSAR analysis of antibody-lysozyme interactions to 3D-QSAR”. 《Biophysical Journal》 84 (4): 2264–72. Apr 2003. Bibcode:2003BpJ....84.2264F. doi:10.1016/S0006-3495(03)75032-2. PMC 1302793. PMID 12668435.
《Handbook of Molecular Descriptors》. Weinheim: Wiley-VCH. 2002. ISBN 3-527-29913-0.
《Pattern classification》. Chichester: John Wiley & Sons. 2001. ISBN 0-471-05669-3.

doi.org

dx.doi.org

Nantasenamat C, Isarankura-Na-Ayudhya C, Prachayasittikul V (Jul 2010). “Advances in computational methods to predict the biological activity of compounds”. 《Expert Opinion on Drug Discovery》 5 (7): 633–54. doi:10.1517/17460441.2010.492827. PMID 22823204.
Yousefinejad S, Hemmateenejad B (2015). “Chemometrics tools in QSAR/QSPR studies: A historical perspective”. 《Chemometrics and Intelligent Laboratory Systems》. 149, Part B: 177–204. doi:10.1016/j.chemolab.2015.06.016.
“The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models”. 《QSAR &Comb. Sci.》 22: 69–77. 2003. doi:10.1002/qsar.200390007.
“Principles of QSAR models validation: internal and external”. 《QSAR &Comb. Sci.》 26: 694–701. 2007. doi:10.1002/qsar.200610151.
“Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection”. 《Journal of Chemical Information and Modeling》 52 (8): 2044–58. Aug 2012. doi:10.1021/ci300084j. PMID 22721530.
Tropsha, Alexander (2010). “Best Practices for QSAR Model Development, Validation, and Exploitation”. 《Molecular Informatics》 29 (6-7): 476–488. doi:10.1002/minf.201000061. ISSN 1868-1743.
“Bioisosterism: A Rational Approach in Drug Design”. 《Chemical Reviews》 96 (8): 3147–3176. Dec 1996. doi:10.1021/cr950066q. PMID 11848856.
“On the hydrophobicity of peptides: Comparing empirical predictions of peptide log P values”. 《Bioinformation》 1 (7): 237–41. 2006. doi:10.6026/97320630001237. PMC 1891704. PMID 17597897.
“Prediction of physicochemical parameters by atomic contributions”. 《J. Chem. Inf. Comput. Sci》 39 (5): 868–873. 1999. doi:10.1021/ci990307l.
“Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies”. 《Journal of Computer-Aided Molecular Design》 24 (10): 843–64. Oct 2010. Bibcode:2010JCAMD..24..843M. doi:10.1007/s10822-010-9378-9. PMID 20740315.
“Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions”. 《Journal of Biomolecular Structure & Dynamics》 33 (1): 56–69. November 2013. doi:10.1080/07391102.2013.849618. PMID 24266725.
“Solving the multiple instance problem with axis-parallel rectangles”. 《Artificial Intelligence》 89 (1–2): 31–71. 1997. doi:10.1016/S0004-3702(96)00034-3.
“Catalyst design: knowledge extraction from high-throughput experimentation”. 《J. Catal.》 216: 3776–3777. 2003. doi:10.1016/S0021-9517(02)00036-2.
“Structure-activity correlation in titanium single-site olefin polymerization catalysts containing mixed cyclopentadienyl/aryloxide ligation”. 《Journal of the American Chemical Society》 129 (13): 3776–7. Apr 2007. doi:10.1021/ja0640849. PMID 17348648.
“Structure–Activity Correlation for Relative Chain Initiation to Propagation Rates in Single-Site Olefin Polymerization Catalysis”. 《Organometallics》 31 (2): 602–618. 2012. doi:10.1021/om200884x.
“In silico prediction of drug toxicity”. 《Journal of Computer-Aided Molecular Design》 17 (2-4): 119–27. 2003. Bibcode:2003JCAMD..17..119D. doi:10.1023/A:1025361621494. PMID 13677480.
“Assessing QSAR Limitations – A Regulatory Perspective”. 《Current Computer-Aided Drug Design》 1 (2): 195–205. April 2005. doi:10.2174/1573409053585663.
“On some aspects of validation of predictive quantitative structure-activity relationship models”. 《Expert Opinion on Drug Discovery》 2 (12): 1567–77. Dec 2007. doi:10.1517/17460441.2.12.1567.
“On selection of training and test sets for the development of predictive QSAR models”. 《QSAR & Combinatorial Science》 25 (3): 235–251. 2006. doi:10.1002/qsar.200510161.
“Exploring the impact of size of training sets for the development of predictive QSAR models”. 《Chemometrics and Intelligent Laboratory Systems》 90 (1): 31–42. 2008. doi:10.1016/j.chemolab.2007.07.004.
“Review on modelling aspects in reversed-phase liquid chromatographic quantitative structure-retention relationships”. 《Analytica Chimica Acta》 602 (2): 164–72. Oct 2007. doi:10.1016/j.aca.2007.09.014. PMID 17933600.
“On two novel parameters for validation of predictive QSAR models”. 《Molecules》 14 (5): 1660–701. 2009. doi:10.3390/molecules14051660. PMID 19471190.
“Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient”. 《Journal of Chemical Information and Modeling》 51 (9): 2320–35. Sep 2011. doi:10.1021/ci200211n. PMID 21800825.
“Structural modeling extends QSAR analysis of antibody-lysozyme interactions to 3D-QSAR”. 《Biophysical Journal》 84 (4): 2264–72. Apr 2003. Bibcode:2003BpJ....84.2264F. doi:10.1016/S0006-3495(03)75032-2. PMC 1302793. PMID 12668435.
“Machine-learning approaches in drug discovery: methods and applications”. 《Drug Discovery Today》 20 (3): 318–31. Mar 2015. doi:10.1016/j.drudis.2014.10.012. PMID 25448759.
“AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment”. 《Journal of Cheminformatics》 3: 28. 2011. doi:10.1186/1758-2946-3-28. PMC 3158423. PMID 21798025.

doi.org

Fraczkiewicz, R (2013). "In Silico Prediction of Ionization". In Reedijk, J. Reference Module in Chemistry, Molecular Sciences and Chemical Engineering [Online]. vol. 5. Amsterdam, The Netherlands: Elsevier. doi:10.1016/B978-0-12-409547-2.02610-X.

harvard.edu

adsabs.harvard.edu

“Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies”. 《Journal of Computer-Aided Molecular Design》 24 (10): 843–64. Oct 2010. Bibcode:2010JCAMD..24..843M. doi:10.1007/s10822-010-9378-9. PMID 20740315.
“In silico prediction of drug toxicity”. 《Journal of Computer-Aided Molecular Design》 17 (2-4): 119–27. 2003. Bibcode:2003JCAMD..17..119D. doi:10.1023/A:1025361621494. PMID 13677480.
“Structural modeling extends QSAR analysis of antibody-lysozyme interactions to 3D-QSAR”. 《Biophysical Journal》 84 (4): 2264–72. Apr 2003. Bibcode:2003BpJ....84.2264F. doi:10.1016/S0006-3495(03)75032-2. PMC 1302793. PMID 12668435.

jcheminf.com

http://www.jcheminf.com/content/6/1/48/

nih.gov

ncbi.nlm.nih.gov

Nantasenamat C, Isarankura-Na-Ayudhya C, Prachayasittikul V (Jul 2010). “Advances in computational methods to predict the biological activity of compounds”. 《Expert Opinion on Drug Discovery》 5 (7): 633–54. doi:10.1517/17460441.2010.492827. PMID 22823204.
“Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection”. 《Journal of Chemical Information and Modeling》 52 (8): 2044–58. Aug 2012. doi:10.1021/ci300084j. PMID 22721530.
“Bioisosterism: A Rational Approach in Drug Design”. 《Chemical Reviews》 96 (8): 3147–3176. Dec 1996. doi:10.1021/cr950066q. PMID 11848856.
“On the hydrophobicity of peptides: Comparing empirical predictions of peptide log P values”. 《Bioinformation》 1 (7): 237–41. 2006. doi:10.6026/97320630001237. PMC 1891704. PMID 17597897.
“Rationalizing fragment based drug discovery for BACE1: insights from FB-QSAR, FB-QSSR, multi objective (MO-QSPR) and MIF studies”. 《Journal of Computer-Aided Molecular Design》 24 (10): 843–64. Oct 2010. Bibcode:2010JCAMD..24..843M. doi:10.1007/s10822-010-9378-9. PMID 20740315.
“Pharmacophore-similarity-based QSAR (PS-QSAR) for group-specific biological activity predictions”. 《Journal of Biomolecular Structure & Dynamics》 33 (1): 56–69. November 2013. doi:10.1080/07391102.2013.849618. PMID 24266725.
“Structure-activity correlation in titanium single-site olefin polymerization catalysts containing mixed cyclopentadienyl/aryloxide ligation”. 《Journal of the American Chemical Society》 129 (13): 3776–7. Apr 2007. doi:10.1021/ja0640849. PMID 17348648.
“In silico prediction of drug toxicity”. 《Journal of Computer-Aided Molecular Design》 17 (2-4): 119–27. 2003. Bibcode:2003JCAMD..17..119D. doi:10.1023/A:1025361621494. PMID 13677480.
“Review on modelling aspects in reversed-phase liquid chromatographic quantitative structure-retention relationships”. 《Analytica Chimica Acta》 602 (2): 164–72. Oct 2007. doi:10.1016/j.aca.2007.09.014. PMID 17933600.
“On two novel parameters for validation of predictive QSAR models”. 《Molecules》 14 (5): 1660–701. 2009. doi:10.3390/molecules14051660. PMID 19471190.
“Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient”. 《Journal of Chemical Information and Modeling》 51 (9): 2320–35. Sep 2011. doi:10.1021/ci200211n. PMID 21800825.
“Structural modeling extends QSAR analysis of antibody-lysozyme interactions to 3D-QSAR”. 《Biophysical Journal》 84 (4): 2264–72. Apr 2003. Bibcode:2003BpJ....84.2264F. doi:10.1016/S0006-3495(03)75032-2. PMC 1302793. PMID 12668435.
“Machine-learning approaches in drug discovery: methods and applications”. 《Drug Discovery Today》 20 (3): 318–31. Mar 2015. doi:10.1016/j.drudis.2014.10.012. PMID 25448759.
“AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment”. 《Journal of Cheminformatics》 3: 28. 2011. doi:10.1186/1758-2946-3-28. PMC 3158423. PMID 21798025.

worldcat.org

Tropsha, Alexander (2010). “Best Practices for QSAR Model Development, Validation, and Exploitation”. 《Molecular Informatics》 29 (6-7): 476–488. doi:10.1002/minf.201000061. ISSN 1868-1743.