Academic literature on the topic 'Cheminformatics and quantitative structure-activity relationships'
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Journal articles on the topic "Cheminformatics and quantitative structure-activity relationships"
Adl, Ammar, Moustafa Zein, and Aboul Ella Hassanien. "PQSAR: The membrane quantitative structure-activity relationships in cheminformatics." Expert Systems with Applications 54 (July 2016): 219–27. http://dx.doi.org/10.1016/j.eswa.2016.01.051.
Full textJavaid, Muhammad, and Muhammad Imran. "Editorial: Topological investigations of chemical networks." Main Group Metal Chemistry 44, no. 1 (January 1, 2021): 267–69. http://dx.doi.org/10.1515/mgmc-2021-0030.
Full textDustigeer, Ghulam, Haidar Ali, Muhammad Imran Khan, and Yu-Ming Chu. "On multiplicative degree based topological indices for planar octahedron networks." Main Group Metal Chemistry 43, no. 1 (January 1, 2020): 219–28. http://dx.doi.org/10.1515/mgmc-2020-0026.
Full textRizwan, Muhammad, Akhlaq Ahmad Bhatti, Muhammad Javaid, and Fahd Jarad. "Some Bounds on Bond Incident Degree Indices with Some Parameters." Mathematical Problems in Engineering 2021 (July 8, 2021): 1–10. http://dx.doi.org/10.1155/2021/8417486.
Full textZheng, Jialin, Shehnaz Akhter, Zahid Iqbal, Muhammad Kashif Shafiq, Adnan Aslam, Muhammad Ishaq, and Muhammad Aamir. "Irregularity Measures of Subdivision Vertex-Edge Join of Graphs." Journal of Chemistry 2021 (January 18, 2021): 1–12. http://dx.doi.org/10.1155/2021/6673221.
Full textLow, Yen S., Ola Caster, Tomas Bergvall, Denis Fourches, Xiaoling Zang, G. Niklas Norén, Ivan Rusyn, Ralph Edwards, and Alexander Tropsha. "Cheminformatics-aided pharmacovigilance: application to Stevens-Johnson Syndrome." Journal of the American Medical Informatics Association 23, no. 5 (October 24, 2015): 968–78. http://dx.doi.org/10.1093/jamia/ocv127.
Full textKrawczyk, Bartosz. "Pattern recognition approach to classifying CYP 2C19 isoform." Open Medicine 7, no. 1 (February 1, 2012): 38–44. http://dx.doi.org/10.2478/s11536-011-0120-3.
Full textWang, Ying, Sumaira Hafeez, Shehnaz Akhter, Zahid Iqbal, and Adnan Aslam. "The Generalized Inverse Sum Indeg Index of Some Graph Operations." Symmetry 14, no. 11 (November 8, 2022): 2349. http://dx.doi.org/10.3390/sym14112349.
Full textMumtaz, Hafiza Bushra, Muhammad Javaid, Hafiz Muhammad Awais, and Ebenezer Bonyah. "Topological Indices of Pent-Heptagonal Nanosheets via M-Polynomials." Journal of Mathematics 2021 (November 12, 2021): 1–13. http://dx.doi.org/10.1155/2021/4863993.
Full textBogdanović, Aleksandra, Anita Lazić, Slavica Grujić, Ivica Dimkić, Slaviša Stanković, and Slobodan Petrović. "Characterisation of twelve newly synthesised N-(substituted phenyl)-2-chloroacetamides with QSAR analysis and antimicrobial activity tests." Archives of Industrial Hygiene and Toxicology 72, no. 1 (March 1, 2021): 70–79. http://dx.doi.org/10.2478/aiht-2021-72-3483.
Full textDissertations / Theses on the topic "Cheminformatics and quantitative structure-activity relationships"
Girschick, Tobias [Verfasser], Burkhard [Akademischer Betreuer] Rost, and Stefan [Akademischer Betreuer] Kramer. "Enhanced Small Molecule Similarity for Quantitative Structure-Activity Relationship Modeling and Cheminformatics Applications / Tobias Girschick. Gutachter: Burkhard Rost ; Stefan Kramer. Betreuer: Burkhard Rost." München : Universitätsbibliothek der TU München, 2014. http://d-nb.info/1052995357/34.
Full textChen, Jonathan Jun Feng. "Data Mining/Machine Learning Techniques for Drug Discovery: Computational and Experimental Pipeline Development." University of Akron / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=akron1524661027035591.
Full textBruce, Craig L. "Classification and interpretation in quantitative structure-activity relationships." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11666/.
Full textMcNeany, T. John. "Non-parametric approaches to quantitative structure-activity relationships." Thesis, University of Nottingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431188.
Full textAndersson, Patrik. "Physico-chemical characteristics and quantitative structure-activity relationships of PCBs." Doctoral thesis, Umeå University, Chemistry, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-17.
Full textThe polychlorinated biphenyls (PCBs) comprise a group of 209 congeners varying in the number of chlorine atoms and substitution patterns. These compounds tend to be biomagnified in foodwebs and have been shown to induce an array of effects in exposed organisms. The structural characteristics of the PCBs influence their potency as well as mechanism of action. In order to assess the biological potency of these compounds a multi-step quantitative structure-activity relationship (QSAR) procedure was used in the project described in this thesis.
The ultraviolet absorption (UV) spectra were measured for all 209 PCBs, and digitised for use as physico-chemical descriptors. Interpretations of the spectra using principal component analysis (PCA) showed the number of ortho chlorine atoms and para-para substitution patterns to be significant. Additional physico-chemical descriptors were derived from semi-empirical calculations. These included various molecular energies, the ionisation potential, electron affinity, dipole moments, and the internal barrier of rotation. The internal barrier of rotation was especially useful for describing the conformation of the PCBs on a continuous scale.
In total 52 physico-chemical descriptors were compiled and analysed by PCA for the tetra- to hepta-chlorinated congeners. The structural variation within these compounds was condensed into four principal properties derived from a PCA for use as design variables in a statistical design to select congeners representative for these homologue-groups. The 20 selected PCBs have been applied to study structure-specific biochemical responses in a number of bioassays, and to study the biomagnification of the PCBs in various fish species.
QSARs were established using partial least squares projections to latent structures (PLS) for the PCBs potency to inhibit intercellular communication, activate respiratory burst, inhibit dopamine uptake in synaptic vesicles, compete with estradiol for binding to estrogen receptors, and induce cytochrome P4501A (CYP1A) related activities. By the systematic use of the designed set of PCBs the biological potency was screened over the chemical domain of the class of compounds. Further, sub-regions of highly potent PCBs were identified for each response measured. For risk assessment of the PCBs potency to induce dioxin-like activities the predicted induction potencies (PIPs) were calculated. In addition, two sets of PCBs were presented that specifically represent congeners of environmental relevance in combination with predicted potency to induce estrogenic and CYP1A related activities.
Cronin, Mark T. D. "Quantitative structure-activity relationships of comparative toxicity to aquatic organisms." Thesis, Liverpool John Moores University, 1990. http://researchonline.ljmu.ac.uk/4989/.
Full textGooch, Carolyn A. "Quantitative structure-activity relationships : a biophysical, chemical and calorimetric study." Thesis, Royal Holloway, University of London, 1988. http://repository.royalholloway.ac.uk/items/26719d55-b208-4995-bef0-92e4f0f80c0e/1/.
Full textRuark, Christopher Daniel. "Quantitative Structure-Activity Relationships for Organophosphates Binding to Trypsin and Chymotrypsin." Wright State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=wright1278010674.
Full textStanforth, Robert William. "Extending K-Means clustering for analysis of quantitative structure activity relationships (QSAR)." Thesis, Birkbeck (University of London), 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500005.
Full textMwense, Mulaisho. "Toxicity prediction of mixtures of organic chemicals using quantitative structure-activity relationships." Thesis, University of Leeds, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418230.
Full textBooks on the topic "Cheminformatics and quantitative structure-activity relationships"
Alexandre, Varnek, Tropsha Alex, and Royal Society of Chemistry (Great Britain)., eds. Chemoinformatics approaches to virtual screening. Cambridge: RSC Pub., 2008.
Find full textInternational Workshop on Quantitative Structure-Activity Relationships in Environmental Sciences (7th 1996 Elsinore, Denmark). Quantitative structure-activity relationships in environmental sciences, VII. Pensacola, Fla: SETAC Press, 1997.
Find full textMager, Peter P. Multivariate chemometrics in QSAR (quantitative structure-activity relationships): A dialogue. Letchworth, Hertfordshire, England: Research Studies Press, 1988.
Find full textReduced rank regression: With applications to quantitative structure-activity relationships. Heidelberg: Physica-Verlag, 1995.
Find full textRoy, Kunal. Quantitative structure-activity relationships in drug design, predictive toxicology, and risk assessment. Hershey PA: Medical Information Science Reference, an imprint of IGI Global, 2015.
Find full textMartin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. Boca Raton: CRC Press/Taylor & Francis, 2010.
Find full textMartin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. Boca Raton, FL: Taylor & Francis, 2010.
Find full text1931-, Karcher W., and Devillers J. 1956-, eds. Practical applications of quantitative structure-activity relationships (QSAR) in environmental chemistry and toxicology. Dordrecht: Kluwer Academic Publishers, 1990.
Find full textMartin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. Boca Raton, FL: Taylor & Francis, 2010.
Find full textQuantitative drug design: A critical introduction. 2nd ed. Boca Raton, FL: Taylor & Francis, 2010.
Find full textBook chapters on the topic "Cheminformatics and quantitative structure-activity relationships"
Kuhn, Max. "Quantitative-Structure Activity Relationship Modeling and Cheminformatics." In Nonclinical Statistics for Pharmaceutical and Biotechnology Industries, 141–55. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23558-5_6.
Full textGarg, Rajni. "Cheminformatics and Comparative Quantitative Structure-Activity Relationship." In ACS Symposium Series, 97–110. Washington, DC: American Chemical Society, 2005. http://dx.doi.org/10.1021/bk-2005-0894.ch007.
Full textKlebe, Gerhard. "Quantitative Structure–Activity Relationships." In Drug Design, 371–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-17907-5_18.
Full textSchmidli, Heinz. "Quantitative Structure Activity Relationships (QSAR)." In Contributions to Statistics, 5–15. Heidelberg: Physica-Verlag HD, 1995. http://dx.doi.org/10.1007/978-3-642-50015-2_2.
Full textGarcía-Sánchez, Mario Omar, Maykel Cruz-Monteagudo, and José L. Medina-Franco. "Quantitative Structure-Epigenetic Activity Relationships." In Challenges and Advances in Computational Chemistry and Physics, 303–38. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56850-8_8.
Full textDavis, Andrew M. "CHAPTER 6. Quantitative Structure–Activity Relationships." In The Handbook of Medicinal Chemistry, 154–83. Cambridge: Royal Society of Chemistry, 2015. http://dx.doi.org/10.1039/9781782621836-00154.
Full textGupta, Satya P. "Quantitative structure-activity relationships of antianginal drugs." In Progress in Drug Research, 121–54. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8319-1_3.
Full textGupta, Satya P. "Quantitative structure - activity relationships of cardiotonic agents." In Progress in Drug Research, 235–82. Basel: Birkhäuser Basel, 2000. http://dx.doi.org/10.1007/978-3-0348-8385-6_7.
Full textKubinyi, Hugo. "Current Problems in Quantitative Structure Activity Relationships." In Physical Property Prediction in Organic Chemistry, 235–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-74140-1_17.
Full textMaguna, F. P., N. B. Okulik, and Eduardo A. Castro. "Quantitative Structure–Activity Relationships of Antimicrobial Compounds." In Handbook of Computational Chemistry, 1343–57. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-0711-5_38.
Full textConference papers on the topic "Cheminformatics and quantitative structure-activity relationships"
Liu, Rong, Robert Rallo, and Yoram Cohen. "Quantitative Structure-Activity-Relationships for cellular uptake of nanoparticles." In 2013 IEEE 13th International Conference on Nanotechnology (IEEE-NANO). IEEE, 2013. http://dx.doi.org/10.1109/nano.2013.6720861.
Full textButkiewicz, Mariusz, Ralf Mueller, Danilo Selic, Eric Dawson, and Jens Meiler. "Application of machine learning approaches on quantitative structure activity relationships." In 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2009. http://dx.doi.org/10.1109/cibcb.2009.4925736.
Full textXu, Jingbo, and Tisong Jing. "Quantitative Structure-Activity Relationships for Oryzias Latipes Gill ATPase Endpoint." In 2008 2nd International Conference on Bioinformatics and Biomedical Engineering (ICBBE '08). IEEE, 2008. http://dx.doi.org/10.1109/icbbe.2008.296.
Full textAl-Amood, Hanoy K., Hanan F. Al-Shamsi, and Hayat H. Abbas. "Quantitative structure-activity relationships of some new beta amino-carbonyl compounds." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2019. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0029650.
Full textKimani, Njogu, Josphat Matasyoh, Marcel Kaiser, Mauro Nogueira, Gustavo Trossini, and Thomas Schmidt. "An extended study on quantitative structure-antitrypanosomal activity relationships of sesquiterpene lactones." In 4th International Electronic Conference on Medicinal Chemistry. Basel, Switzerland: MDPI, 2018. http://dx.doi.org/10.3390/ecmc-4-05591.
Full textEdgar, Julie A., and Susie Hurley. "The Use of Quantitative Structure Activity Relationships (QSAR) in Traction Fluid Design." In 2004 SAE Fuels & Lubricants Meeting & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2004. http://dx.doi.org/10.4271/2004-01-2009.
Full textLABUTE, P. "BINARY QSAR: A NEW METHOD FOR THE DETERMINATION OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 1998. http://dx.doi.org/10.1142/9789814447300_0044.
Full textGackowski, Marcin, Karolina Szewczyk-Golec, and Marcin Koba. "MARSplines Approach for Quantitative Relationships between Structure and Pharmacological Activity of Potential Drug Candidates." In ECMC 2022. Basel Switzerland: MDPI, 2022. http://dx.doi.org/10.3390/ecmc2022-13170.
Full textHoekman, Leo, Peng Li, Litai Zhang, and Hansch. "A comprehensive approach to database management of quantitative structure-activity relationships (QSAR) in chemistry and biology." In Proceedings of the Twenty-Seventh Annual Hawaii International Conference on System Sciences. IEEE Comput. Soc. Press, 1994. http://dx.doi.org/10.1109/hicss.1994.323577.
Full textStitou, Mourad, Hamid Toufik, Mohammed Bouachrine, Hssain Bih, and Fatima Lamchouri. "Machine learning algorithms used in Quantitative structure-activity relationships studies as new approaches in drug discovery." In 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS). IEEE, 2019. http://dx.doi.org/10.1109/isacs48493.2019.9068917.
Full textReports on the topic "Cheminformatics and quantitative structure-activity relationships"
Turner, J. E. (Quantitative structure-activity relationships in environmental toxicology). Office of Scientific and Technical Information (OSTI), October 1990. http://dx.doi.org/10.2172/6613721.
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