Relevant bibliographies by topics / Quantitative Structure-Activity Relationship [MESH]

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Quantitative Structure-Activity Relationship [MESH]'

Author: Grafiati
Published: 29 July 2024
Last updated: 31 July 2025

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Journal articles on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Lin, Yu-Liang, Peng-Fei Fang, Xin Wang, Jie Wu, and Guo-Lin Yang. "Experimental and Numerical Study on Tensile Behavior of Double-Twisted Hexagonal Gabion Wire Mesh." Buildings 13, no. 7 (2023): 1657. http://dx.doi.org/10.3390/buildings13071657.

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Double-twisted hexagonal gabion wire mesh is a type of reinforced soil material that is used in gabion retaining walls to stabilize the soil slope in geotechnical engineering. In this study, a series of tensile tests were conducted to investigate the tensile behavior of hexagonal gabion wire mesh. Meanwhile, numerical models of gabion wire mesh were built to investigate the whole tensile loading-strain process. The influence of wire diameter, mesh width, and mesh length on the tensile strength of hexagonal gabion wire mesh were evaluated based on laboratory tests and numerical simulation. The
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Ilyushchanka, Aliaksandr, Iryna Charniak, Aliaksei Kusin, Mihail Dechko, Ruslan Kusin, and Natalia Rutkovskaia. "Selection of factors and preparation of an experiment planning matrix for modeling a filter material with an orthotropic structure based on woven meshes." MATEC Web of Conferences 366 (2022): 05001. http://dx.doi.org/10.1051/matecconf/202236605001.

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The advantages of a filtering material with an orthotropic structure (FMTS) consisting of a package of woven meshes are described. Information is given on the first stage of FMTS modeling, which includes the choice of parameters and factors of the experiment and the compilation of a planning matrix to establish the relationship between technological characteristics and properties of FMTS. When constructing a stochastic mathematical model at this stage, two factors were chosen to describe the properties of the material – qualitative (mesh type), specified by the sigma constraint method, and qua
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Pereira Gomes, Dione, and Aníbal Danilo Farias. "Systematic review on the relationship between left heart failure and right ventricular dysfunction in the 2000s." SCT Proceedings in Interdisciplinary Insights and Innovations 1 (November 10, 2023): 143. http://dx.doi.org/10.56294/piii2023143.

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Background: Heart failure is a clinical syndrome characterized by symptoms such as dyspnea and fluid retention in the context of structural abnormalities of the heart. For many years, the importance of the right heart was ignored or forgotten, however, it has been revealed that the right ventricle is a key part in the prognosis of left heart failure. The right ventricle modulates the structure and function of the left ventricle. Interest arises in carrying out a bibliographic review on right heart failure as a cause of left heart failure. Material and methods: The study design was a systematic
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Liu, Jin Tao, Wei Shen, Qun Bo Fan, and H. N. Cai. "Modeling the Cracking Process of the YSZ Thermal Barrier Coating under the Thermal Shocking Loads." Key Engineering Materials 512-515 (June 2012): 463–68. http://dx.doi.org/10.4028/www.scientific.net/kem.512-515.463.

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For low thermal conductivity and high corrosion resistance, yttria stabilized zirconia (YSZ), as a top coat (TC), is widely used in thermal barrier coatings (TBCs), and the micro-structure of the TC has significant effects on it thermal shock resistance. Combining digital image processing technique with finite element mesh generation methods, finite element (EF) models based on actual microstructures of plasma sprayed YSZ thermal barrier coatings are built in this paper, so as to simulate the coating’s dynamic failure process when suffering thermal shocking loads. The cracking process is revea
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Huang, Shunjie, Xiangqian Wang, Yingming Li, et al. "Analysis on Evolution Law of Small Structure Stress Arch and Composite Bearing Arch in Island Gob-Side Entry Driving." Geofluids 2022 (June 23, 2022): 1–12. http://dx.doi.org/10.1155/2022/4303681.

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At present, the theory of supporting the surrounding rock small structure of gob-side entry driving has been widely used, but there is no specific quantitative analytical formula for the bearing strength and bearing characteristics of the structure. Construct a small structural stress arch mechanical model based on the arch axis equation, and divide the width of coal pillars (fractured zone-plastic softening zone-plastic hardening zone) and small structural stress arch height. According to the relationship between the stress arch height and the size of the roadway, the anchor cable length is d
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Golubenko, Daniil, Farah Ejaz Ahmed, and Nidal Hilal. "Novel Crosslinked Anion Exchange Membranes Based on Thermally Cured Epoxy Resin: Synthesis, Structure and Mechanical and Ion Transport Properties." Membranes 14, no. 6 (2024): 138. http://dx.doi.org/10.3390/membranes14060138.

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Limitations in existing anion exchange membranes deter their use in the efficient treatment of industrial wastewater effluent. This work presents an approach to fabricating novel anion-conducting membranes using epoxy resin monomers like hydrophobic or hydrophilic diglycidyl ether and quaternized polyethyleneimine (PEI). Manipulating the diglycidyl ether nature, the quantitative composition of the copolymer and the conditions of quaternization allows control of the physicochemical properties of the membranes, including water uptake (20.0–330%), ion exchange capacity (1.5–3.7 mmol/g), ionic con
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Matsuda, Atsushi, and Mohammad R. K. Mofrad. "Role of pore dilation in molecular transport through the nuclear pore complex: Insights from polymer scaling theory." PLOS Computational Biology 21, no. 4 (2025): e1012909. https://doi.org/10.1371/journal.pcbi.1012909.

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The nuclear pore complex (NPC), a channel within the nuclear envelope filled with intrinsically disordered proteins, regulates the transport of macromolecules between the nucleus and the cytoplasm. Recent studies have highlighted the NPC’s ability to adjust its diameter in response to the membrane tension, underscoring the importance of exploring how variations in pore size influence molecular transport through the NPC. In this study, we investigated the relationship between pore size and transport rate and proposed a mathematical model describing this connection. We began by theoretically ana
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NAKAGAWA, Yoshiaki. "Quantitative Structure-Activity Relationship." Japanese Journal of Pesticide Science 38, no. 1 (2013): 1. http://dx.doi.org/10.1584/jpestics.w12-39.

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Seregin, S. A. "Some peculiarities in vertical distribution of metazoan microzooplankton in the Black Sea in spring." Marine Biological Journal 5, no. 4 (2020): 94–107. http://dx.doi.org/10.21072/mbj.2020.05.4.08.

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Based on material, received in the 84th and 93rd cruises of the RV “Professor Vodyanitsky”, vertical distribution of microplankton fraction of metazooplankton (MM) in the Black Sea in spring was analyzed. A total of 27 stations were examined both in the coastal zone and in the deep sea. The 10-L bottles of the CTD probes “Mark-III Neil Brown” and “Sea Bird 911” were used to collect 4–6 L of water from 4–11 horizons of the water column. The samples obtained were concentrated by the reverse filtration through the plankton net with the mesh size of 10 µm. Quantitative and systematic analysis of a
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FUJITA, Toshio. "Quantitative structure-activity relationship and drug design." Journal of the agricultural chemical society of Japan 64, no. 1 (1990): 1–11. http://dx.doi.org/10.1271/nogeikagaku1924.64.1.

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Dissertations / Theses on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Li, Ju-Yun. "Quantitative structure-activity relationship studies in medicinal chemistry." Case Western Reserve University School of Graduate Studies / OhioLINK, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=case1062596938.

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Reddy, Badinehal Asrith. "COMMERCIALIZATION OF A QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP TOOL - SARCHITECT." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1295637833.

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Ren, Xin. "Quantitative structure-activity relationship based virtual screening for novel androgen receptor antagonists." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/43293.

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Androgen receptor (AR) plays a critical role in prostate cancer development and progression. All current therapeutic AR inhibitors modulate the receptor via direct binding to its Hormone Binding Site (HBS). Despite the identification of other small molecule binding areas on the AR surface including Activation Function 2 (AF2), binding function 3 (BF3), and N-terminal domain (NTD), HBS continues to be the major target site for AR antagonists (even though this site is prone to resistant mutations). Thus, there is a high need for the identification and development of novel antagonists targeting H
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Smith, Mark David. "A quantitative structure-activity relationship (QSAR) study of the Ames mutagenicity assay." Thesis, University of Portsmouth, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343333.

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In-vitro mutagenicity assays have traditionally been used for first line identification of potential genotoxic hazard, purporting to chemical carcinogenesis and heritable genetic damage. The recent advances m combinatorial chemistry and high throughput screening technologies have led to a massive explosion in numbers of possible therapeutic candidates being produced at the early stages of drug discovery. This rapid increase in the number of chemicals to be classified results in a greater need for to acquire alternative methods for the prediction of toxicity. Quantitative StructureActivity Rela
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Lanevskij, Kiril. "Absorption and Tissue Distribution of Drug-Like Compounds: Quantitative Structure-Activity Relationship Analysis." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2011. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2011~D_20111003_114235-89858.

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The objective of this work was to develop mechanistic quantitative structure activity relationship models that would facilitate the assessment of drug properties related to their absorption and distribution in the body. The analysis involved several parameters reflecting the rate of passive diffusion across brain endothelium and intestinal epithelium, and thermodynamic constants related to drug distribution between plasma and tissues. Permeation through cellular transport barriers was modeled by nonlinear equations relating the passive diffusion rate to physicochemical properties of drugs: lip
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Ruark, 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.

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Diaz-Perez, Maria-Jose. "Quantitative structure-activity relationship (QSAR) study of the effect of steroids on DNA replication." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ50291.pdf.

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Peron, Jean-Marie. "Quantitative structure activity relationship analysis of anti-oxidants with central nervous system therapeutic potential." Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271327.

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Jaafar, Mohd Zuli. "Chemometrics and pattern recognition methods with applications to environmental and quantitative structure-activity relationship studies." Thesis, University of Bristol, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541608.

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Marsden-Jones, Siân Catherine. "The application of quantitative structure activity relationship models to the method development of countercurrent chromatography." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/12598.

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A fundamental challenge for liquid-liquid separation techniques such as countercurrent chromatography (CCC)and centrifugal partition chromatography (CPC), is the swift, efficient selection of the two phase solvent system containing more than two solvents, for the purification of pharmaceuticals and other molecules. A purely computational model that could predict the optimal solvent systems for separation using just molecular structure would be ideal for this task. The experimental value being predicted is the partition coefficient (Kd), which is the concentration of the compound in one phase d
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Books on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076.

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Alexandre, Varnek, Tropsha Alex, and Royal Society of Chemistry (Great Britain)., eds. Chemoinformatics approaches to virtual screening. RSC Pub., 2008.

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name, No. Quantitative structure-activity relationship (QSAR) models of mutagens and carcinogens. CRC Press, 2002.

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Romualdo, Benigni, ed. Quantitative structure-activity relationship (QSAR) models of mutagens and carcinogens. CRC Press, 2003.

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Smith, Mark David. A quantitative structure-activity relationship (QSAR) study of the Ames mutagenicity assay. [University of Portsmouth?], 2000.

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Martin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. CRC Press/Taylor & Francis, 2010.

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Martin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. Taylor & Francis, 2010.

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Martin, Yvonne Connolly. Quantitative drug design: A critical introduction. 2nd ed. Taylor & Francis, 2010.

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Roy, Kunal. Quantitative structure-activity relationships in drug design, predictive toxicology, and risk assessment. Medical Information Science Reference, an imprint of IGI Global, 2015.

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1956-, Devillers J., and Balaban Alexandru T, eds. Topological indices and related descriptors in QSAR and QSPR. Gordon and Breach, 1999.

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Book chapters on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Bajorath, Jürgen. "Quantitative Structure Activity Relationship." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27841-9_4882-2.

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Bajorath, Jürgen. "Quantitative Structure Activity Relationship." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-46875-3_4882.

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Bajorath, Jürgen. "Quantitative Structure Activity Relationship." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16483-5_4882.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "QSAR at a Glance." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-1.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Database and Dataset." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-2.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Molecular Descriptors." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-3.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Descriptor Selection." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-4.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Model Building." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-5.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Validation of QSAR Models." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-6.

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Dastmalchi, Siavoush, Maryam Hamzeh-Mivehroud, and Babak Sokouti. "Practical Example." In Quantitative Structure–Activity Relationship. CRC Press, 2018. http://dx.doi.org/10.1201/9781351113076-7.

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Conference papers on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Du, Zhenjiao, and Yonghui Li. "Quantitative Structure-activity Relationship Study on Antioxidant Dipeptides." In 2022 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2022. http://dx.doi.org/10.21748/cpyc1755.

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Antioxidative peptides have attracted increasing interest of researchers and consumers. Compared to wet chemistry methods, quantitative structure-activity relationship (QSAR) analysis as a in silicon method can be more efficient and cost effective and has been successfully applied to activity prediction of angiotensin I-converting enzyme inhibitory activity and bitterness of peptides. However, there are only few QSAR studies on antioxidative activity, particularly for dipeptides which have demonstrated ideal absorption ability in intestinal compared to larger peptides. This study aimed to cond
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Luo, Huajun, Junzhi Wang, Yuan Zhou, and Kun Zou. "Quantitative Structure-Activity Relationship of Sesquiterpene Lactones with Anti-Ulcerogenic Activity." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163275.

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Zhao, Li-Jiao, Ru-Gang Zhong, and Yan Zhen. "Quantitative Structure-Activity Relationship Analysis of the Anticancer Activity of Chloroethylnitrosourea Derivatives." In 2007 1st International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/icbbe.2007.316.

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Li, Xiao-Li, Min Li, Zheng Ke, Hua-Jun Luo, and Wei-Qiao Deng. "Quantitative Structure-Activity Relationship Model of Lenalidomide Analogues as TNF-Inhibitors." In 2013 Fifth International Conference on Computational and Information Sciences (ICCIS). IEEE, 2013. http://dx.doi.org/10.1109/iccis.2013.36.

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Neophytou, Katerina, Christos A. Nicolaou, Constantinos S. Pattichis, and Christos N. Schizas. "Deriving Quantitative Structure-Activity Relationship Models Using Genetic Programming for Drug Discovery." In 6th International Special Topic Conference on Information Technology Applications in Biomedicine, 2007. IEEE, 2007. http://dx.doi.org/10.1109/itab.2007.4407401.

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Triatmaja, K., SY Prabawati, and PD Widiakongko. "QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP (QSAR) STUDY OF EUGENOL DERIVATIVES AS ANTIOXIDANT COMPOUNDS." In International conference on food, nutrition, health and lifestyle. The International Institute of Knowledge Management, 2022. http://dx.doi.org/10.17501/26827026.2022.1102.

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Zhao Li-Jiao, Zhong Ru-Gang, Zhen Yan, and Dai Qian-Huan. "Research on the Quantitative Structure-Carcinogenic Activity Relationship of N-Nitroso Compounds." In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1615532.

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S, Sushma, Nithish Sundaram, and N. Jayapandian. "Machine learning based Unique Perfume Flavour Creation Using Quantitative Structure-Activity Relationship (QSAR)." In 2021 5th International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2021. http://dx.doi.org/10.1109/iccmc51019.2021.9418246.

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Ridzuan, M. S. M., M. Z. Jaafar, and M. M. Zain. "Quantitative structure-activity relationship (QSAR) modelling of N-aryl derivatives as cholinesterase inhibitors." In 2012 IEEE Symposium on Humanities, Science and Engineering Research (SHUSER). IEEE, 2012. http://dx.doi.org/10.1109/shuser.2012.6269006.

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Lu, Rong, Hai-xia Ma, Wei-ping Liu, and Wen-xin Li. "Studies on quantitative structure-activity-relationship inhibitory effects of benzoic acid derivatives on tyrosinase." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5516550.

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Reports on the topic "Quantitative Structure-Activity Relationship [MESH]"

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Ruangpornvisuti, Vithaya. A Study of conformational equilibrium of semicarbazone derivatives and their complexes with cations : research report. Chulalongkorn University, 2006. https://doi.org/10.58837/chula.res.2006.36.

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The structure optimizations of picolinaldehyde N-oxide thiosemicarbazone (Hpiotsc), 2-benzoylpyridine semicarbazone (H2BzPS), their imino tautomers and their complexes with Ni(II), Cu(II) and Zn(II) were carried out using DFT calculations at the B3LYP/LANL2DZ level of theory. Thermodynamic properties of tautomerizations of Hpiotsc and H2BzPS and complexations of their complexes derived from the frequency calculations at the same level were obtained. The B3LYP/LANL2DZ-optimized geometry parameters for the complexes of [[Ni(Hpiotsc)[subscript 2]][superscript 2+]], [Cu(Hpiotsc).Cl[subscript 2]] a
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Dashtey, Ahmed, Patrick Mormile, Sandra Pedre, Stephany Valdaliso, and Walter Tang. Prediction of PFOA and PFOS Toxicity through Log P and Number of Carbon with CompTox and Machine Learning Tools. Florida International University, 2024. http://dx.doi.org/10.25148/ceefac.2024.00202400.

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Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are two major groups of PFAS will be subjected to the Maximal Contamination Concentration (MCL) of 4 ng/l in drinking water to be implemented by the U.S. EPA by 2025. How to accurately predict toxicity of PFAS with varied carbon chain length is important for treatment and sequential removal from drinking water. This study presents Quantitative Structure and Activity Relationship (QSAR) models developed through both linear regression and two order regression. Log P is compiled from reference and carbon content is counted as
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