QSRR analysis in characterization of some benzimidazole derivatives
In this paper, quantitative structure-retention relationship study has been applied in order to correlate obtained retention parameter RM0 and two groups of molecular descriptors, for eleven investigated benzimidazole derivatives. Principal component analysis (PCA), followed by hierarchical cluster...
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| Format: | Article |
| Language: | English |
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Slovenian Chemical Society
2015-11-01
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| Series: | Acta Chimica Slovenica |
| Subjects: | |
| Online Access: | https://journals.matheo.si/index.php/ACSi/article/view/1134 |
| _version_ | 1819102135728472064 |
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| author | Milica Karadžić Sanja Podunavac-Kuzmanović Lidija Jevrić Strahinja Kovačević |
| author_facet | Milica Karadžić Sanja Podunavac-Kuzmanović Lidija Jevrić Strahinja Kovačević |
| author_sort | Milica Karadžić |
| collection | DOAJ |
| description | In this paper, quantitative structure-retention relationship study has been applied in order to correlate obtained retention parameter RM0 and two groups of molecular descriptors, for eleven investigated benzimidazole derivatives. Principal component analysis (PCA), followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR), was applied in order to identify the most important molecular descriptors. Mathematical models were established and the best models were further validated by leave-on-out (LOO) technique as well as by the calculation of the statistical parameters. Statistically significant models were established. |
| first_indexed | 2024-12-22T01:29:45Z |
| format | Article |
| id | doaj.art-f10313d3b5d54f42aefed6dd7686de11 |
| institution | Directory Open Access Journal |
| issn | 1318-0207 1580-3155 |
| language | English |
| last_indexed | 2024-12-22T01:29:45Z |
| publishDate | 2015-11-01 |
| publisher | Slovenian Chemical Society |
| record_format | Article |
| series | Acta Chimica Slovenica |
| spelling | doaj.art-f10313d3b5d54f42aefed6dd7686de112022-12-21T18:43:31ZengSlovenian Chemical SocietyActa Chimica Slovenica1318-02071580-31552015-11-0162474775310.17344/acsi.2014.1134301QSRR analysis in characterization of some benzimidazole derivativesMilica Karadžić0Sanja Podunavac-Kuzmanović1Lidija Jevrić2Strahinja Kovačević3University of Novi Sad, Faculty of TechnologyUniversity of Novi Sad, Faculty of TechnologyUniversity of Novi Sad, Faculty of TechnologyUniversity of Novi Sad, Faculty of TechnologyIn this paper, quantitative structure-retention relationship study has been applied in order to correlate obtained retention parameter RM0 and two groups of molecular descriptors, for eleven investigated benzimidazole derivatives. Principal component analysis (PCA), followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR), was applied in order to identify the most important molecular descriptors. Mathematical models were established and the best models were further validated by leave-on-out (LOO) technique as well as by the calculation of the statistical parameters. Statistically significant models were established.https://journals.matheo.si/index.php/ACSi/article/view/1134benzimidazolemultiple linear regressionprincipal component analysishierarchical cluster analysis |
| spellingShingle | Milica Karadžić Sanja Podunavac-Kuzmanović Lidija Jevrić Strahinja Kovačević QSRR analysis in characterization of some benzimidazole derivatives Acta Chimica Slovenica benzimidazole multiple linear regression principal component analysis hierarchical cluster analysis |
| title | QSRR analysis in characterization of some benzimidazole derivatives |
| title_full | QSRR analysis in characterization of some benzimidazole derivatives |
| title_fullStr | QSRR analysis in characterization of some benzimidazole derivatives |
| title_full_unstemmed | QSRR analysis in characterization of some benzimidazole derivatives |
| title_short | QSRR analysis in characterization of some benzimidazole derivatives |
| title_sort | qsrr analysis in characterization of some benzimidazole derivatives |
| topic | benzimidazole multiple linear regression principal component analysis hierarchical cluster analysis |
| url | https://journals.matheo.si/index.php/ACSi/article/view/1134 |
| work_keys_str_mv | AT milicakaradzic qsrranalysisincharacterizationofsomebenzimidazolederivatives AT sanjapodunavackuzmanovic qsrranalysisincharacterizationofsomebenzimidazolederivatives AT lidijajevric qsrranalysisincharacterizationofsomebenzimidazolederivatives AT strahinjakovacevic qsrranalysisincharacterizationofsomebenzimidazolederivatives |