کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6330780 1619785 2014 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Methods for assigning confidence to toxicity data with multiple values - Identifying experimental outliers
ترجمه فارسی عنوان
روش های تعیین اعتماد به داده های سمیت با مقادیر متعدد - شناسایی حوادث تجربی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست شیمی زیست محیطی
چکیده انگلیسی
The assessment of data quality is a crucial element in many disciplines such as predictive toxicology and risk assessment. Currently, the reliability of toxicity data is assessed on the basis of testing information alone (adherence to Good Laboratory Practice (GLP), detailed testing protocols, etc.). Common practice is to take one toxicity data point per compound - usually the one with the apparently highest reliability. All other toxicity data points (for the same experiment and compound) from other sources are neglected. To show the benefits of incorporating the “less reliable” data, a simple, independent, statistical approach to assess data quality and reliability on a mathematical basis was developed. A large data set of toxicity values to Aliivibrio fischeri was assessed. The data set contained 1813 data points for 1227 different compounds, including 203 identified as non-polar narcotic. Log KOW values were calculated and non-polar narcosis quantitative structure-activity relationship (QSAR) models were built. A statistical approach to data quality assessment, which is based on data outlier omission and confidence scoring, improved the linear QSARs. The results indicate that a beneficial method for using large data sets containing multiple data values per compound and highly variable study data has been developed. Furthermore this statistical approach can help to develop novel QSARs and support risk assessment by obtaining more reliable values for biological endpoints.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Science of The Total Environment - Volumes 482–483, 1 June 2014, Pages 358-365
نویسندگان
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