A two-phase solution procedure using mixtures of algorithms in the structure–property problem
Prediction of the properties of chemical compounds by mathematical methods of pattern recognition is considered. The investigation was carried out by the example of the activity of cell division enzyme inhibitors. An approach based on mixtures of algorithms is used as the method for the construction...
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Published in | Pattern recognition and image analysis Vol. 26; no. 2; pp. 427 - 433 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Moscow
Pleiades Publishing
01.04.2016
Springer Nature B.V |
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Abstract | Prediction of the properties of chemical compounds by mathematical methods of pattern recognition is considered. The investigation was carried out by the example of the activity of cell division enzyme inhibitors. An approach based on mixtures of algorithms is used as the method for the construction of recognition models. A two-phase solution procedure for the structure–property problem is analyzed. The local classifier based on the nearest neighbor algorithm and the method of clustering sets is also described. New algorithms for the construction of classifier mixtures are compared. The methods of coordinated prediction of the activity of new compounds are examined. A comparison of mathematical modeling results with molecular design methods based on the coordination of compounds with known structures of therapeutic targets is also presented. An experimental study of the biological activity is conducted. |
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AbstractList | Prediction of the properties of chemical compounds by mathematical methods of pattern recognition is considered. The investigation was carried out by the example of the activity of cell division enzyme inhibitors. An approach based on mixtures of algorithms is used as the method for the construction of recognition models. A two-phase solution procedure for the structure-property problem is analyzed. The local classifier based on the nearest neighbor algorithm and the method of clustering sets is also described. New algorithms for the construction of classifier mixtures are compared. The methods of coordinated prediction of the activity of new compounds are examined. A comparison of mathematical modeling results with molecular design methods based on the coordination of compounds with known structures of therapeutic targets is also presented. An experimental study of the biological activity is conducted. |
Author | Svitan’ko, I. V. Prokhorov, E. I. Bekker, A. V. Zakharenko, A. L. Perevoznikov, A. V. Kumskov, M. I. Sukhanova, M. V. |
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Keywords | docking mixture of algorithms QSAR (Quantitative Structure-Activity Relationship) clustering classification structure–property problem pattern recognition |
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The Way to Predict Properties and Biological Activity of Chemical Compounds contributor: fullname: Bekker – volume: 22 start-page: 15 issue: 1 year: 2012 end-page: 17 ident: CR19 article-title: Rational design and synthesis of new PARP1 inhibitors publication-title: Mendeleev Commun. doi: 10.1016/j.mencom.2012.01.005 contributor: fullname: Svitan’ko – start-page: 25 year: 2012 end-page: 56 ident: CR1 article-title: Consistent prediction of anticancer activity according to “structure-property” models family publication-title: The Way to Predict Chemical States properties. Unified Information Repository for “Structure-Property” Models. Collection of Scientific Papers contributor: fullname: Apryshko – ident: CR11 – volume: 10 start-page: 46 year: 2012 end-page: 56 ident: CR10 article-title: Neuron networks for creating validity constraints in “structure-property” problem publication-title: Neirokomp’yut. Razrab. Primen. contributor: fullname: Prokhorov – volume: 48 start-page: 2371 issue: 12 year: 2008 end-page: 2385 ident: CR18 article-title: Lead finder: an approach to improve accuracy of protein-ligand docking, binding energy estimation, and virtual screening publication-title: J. Chem. Inf. Model doi: 10.1021/ci800166p contributor: fullname: Chilov – volume: 36 start-page: 111 year: 1974 end-page: 147 ident: CR13 article-title: Cross-validatory choice and assessment of statistical predictions publication-title: J. Roy. Stat. Soc. 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Rastrigin – volume: 336 start-page: 64 issue: 1 year: 1994 ident: 4691_CR12 publication-title: Dokl. Akad. Nauk contributor: fullname: M. I. Kumskov – start-page: 337 volume-title: Proc. 24th SIBGRAPI Conf. on Graphics, Patterns and Images year: 2011 ident: 4691_CR17 contributor: fullname: R. Thomas – volume: 4 start-page: 127 year: 1996 ident: 4691_CR14 publication-title: Probl. Upravlen. Inf. contributor: fullname: M. I. Kumskov – volume: 33 start-page: 5 year: 1978 ident: 4691_CR4 publication-title: Probl. Kibernet. contributor: fullname: Yu. I. Zhuravlev – volume: 48 start-page: 2371 issue: 12 year: 2008 ident: 4691_CR18 publication-title: J. Chem. Inf. Model doi: 10.1021/ci800166p contributor: fullname: O. V. Stroganov – volume: 36 start-page: 111 year: 1974 ident: 4691_CR13 publication-title: J. Roy. Stat. Soc. B contributor: fullname: M. Stone – start-page: 25 volume-title: The Way to Predict Chemical States properties. Unified Information Repository for “Structure-Property” Models. Collection of Scientific Papers year: 2012 ident: 4691_CR1 contributor: fullname: E. I. Prokhorov – volume: 10 start-page: 46 year: 2012 ident: 4691_CR10 publication-title: Neirokomp’yut. Razrab. Primen. contributor: fullname: E. I. Prokhorov – volume: 21 start-page: 545 issue: 3 year: 2011 ident: 4691_CR9 publication-title: Pattern Recogn. Image Anal. doi: 10.1134/S1054661811020866 contributor: fullname: A. V. Perevoznikov – volume-title: Survey of Clustering Data Mining Techniques year: 2002 ident: 4691_CR15 contributor: fullname: P. Berkhin – volume-title: The Nature of Statistical Learning Theory year: 1998 ident: 4691_CR16 contributor: fullname: V. N. Vapnik – volume-title: “Fuzzy” Prediction of Chemical Compounds Properties. Fuzzy Function Usage at Training Set’s Clusters in “Structure-Property” Problem year: 2012 ident: 4691_CR3 contributor: fullname: E. I. 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SubjectTerms | Algorithms Analysis Applied Problems Biological activity Cell division Chemical compounds Classification Classifiers Cluster analysis Clustering Computer Science Construction Design analysis Enzymes Image Processing and Computer Vision Mathematical models Methods Pattern Recognition Studies |
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Title | A two-phase solution procedure using mixtures of algorithms in the structure–property problem |
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