A Stoichiometric Approach to Quantitative Structure−Property Relationships (QSPR)
An unusual analogy between the quantitative structure−property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to...
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Published in | Journal of Chemical Information and Computer Sciences Vol. 43; no. 4; pp. 1259 - 1268 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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United States
American Chemical Society
01.07.2003
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Abstract | An unusual analogy between the quantitative structure−property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers. |
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AbstractList | An unusual analogy between the quantitative structure-property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers.An unusual analogy between the quantitative structure-property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers. An unusual analogy between the quantitative structure-property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers. An unusual analogy between the quantitative structure−property relationships (QSPR), stoichiometry, chemical thermodynamics, and kinetics is presented. Namely, the conventional ordinary least-squares (OLS) QSPR analysis is modified so as to explicitly minimize the residuals of the species subject to a set of linear relations among the residuals. The ways the linear relations among the residuals are visualized and defined totally resemble the formalism of chemical stoichiometry and, therefore, were called isostructural reactions. It is further proved that the residuals may be uniquely partitioned into a sum of contributions associated with a set of isostructural reactions that have the same properties as the response reactions (RERs) previously deduced by us from chemical thermodynamics and kinetics. This finding is shown to be a useful tool for a deeper understanding of the QSPR. In particular, the isostructural RERs approach may be effectively used to detect the outliers. |
Author | Fishtik, Ilie Datta, Ravindra |
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CitedBy_id | crossref_primary_10_1021_jp045863j crossref_primary_10_1021_jp0649753 crossref_primary_10_19261_cjm_2020_803 crossref_primary_10_1021_jp036768y crossref_primary_10_1002_chin_200340232 crossref_primary_10_1021_jp035080i crossref_primary_10_1016_j_cplett_2005_10_003 crossref_primary_10_1021_jp050266y crossref_primary_10_1021_jp0487511 |
Cites_doi | 10.1016/S0009-2509(00)00050-6 10.1039/FT9969203525 10.1002/9781118625590 |
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Title | A Stoichiometric Approach to Quantitative Structure−Property Relationships (QSPR) |
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