Biodegradation: Expert Systems

Klopman, Gilles; Tu, Meihua

doi:10.1002/0470845015.cea022m

Cited by 1 publication

(2 citation statements)

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“…However, many authors noted the lack of the first two descriptor types for QSBR purposes, especially for diverse molecules. Redundancy and low discriminative power of those descriptors determine the situation, because often a small structure modification of a chemical can change its degradation ability appreciably [2,33]. Only for sets of homogeneous compounds some success has been obtained.…”

Section: Qsbr Analysismentioning

confidence: 99%

“…Unfortunately, its modeling is extremely complex, due to a quantity of reaction mechanisms for environmental degradation. On the other hand, the usage of the Quantitative Structure-Biodegradation Relationship (QSBR) [1,2] techniques is a reasonable alternative way for developing of so-called "Expert Systems" for estimation of the environmental degradability. QSBR approaches are based on the postulation that the degradation ability of the compound can be described by some kind of modeling function of numerical descriptors representing the molecular structure.…”

Section: Introductionmentioning

confidence: 99%

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Pesticide Persistence in the Environment - Collected Data and Structure-Based Analysis

Alikhanidi

Takahashi

2004

J. Comput. Chem. Jpn.

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A data set of 420 pesticide persistences in the environment was collected as field half-life (HL) using several on-line databases. Due to the fuzziness of observed values, the compounds were grouped into three major categories: class 1 when a pesticide has HL 30 days; class 2, if 30 < HL 100 days; and class 3, if HL > 100 days. The Quantitative Structure-Biodegradation Relationship (QSBR) analysis was worked out on the training set of 315 pesticides. Thirty one topological substructural descriptors were used and the decision tree approach was employed for the modeling. Estimation results were as follows: for the train set, 5 compounds of two-unity (class 1/class 3) misclassification, 38 compounds of unity (class 1/class 2 and class 2/class 3) misclassification, and 272 compounds (86.3%) were correctly classified; for the test set, there were 3, 20, and 82 compounds (78.1%) respectively. The computer expert system EKeeper was developed on the basis of the QSBR model.

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Section: Qsbr Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%