FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2157851318> ?p ?o ?g. }

• W2157851318 endingPage "784" @default.
• W2157851318 startingPage "766" @default.
• W2157851318 abstract "Selecting most rigorous quantitative structure-activity relationship (QSAR) approaches is of great importance in the development of robust and predictive models of chemical toxicity. To address this issue in a systematic way, we have formed an international virtual collaboratory consisting of six independent groups with shared interests in computational chemical toxicology. We have compiled an aqueous toxicity data set containing 983 unique compounds tested in the same laboratory over a decade against Tetrahymena pyriformis. A modeling set including 644 compounds was selected randomly from the original set and distributed to all groups that used their own QSAR tools for model development. The remaining 339 compounds in the original set (external set I) as well as 110 additional compounds (external set II) published recently by the same laboratory (after this computational study was already in progress) were used as two independent validation sets to assess the external predictive power of individual models. In total, our virtual collaboratory has developed 15 different types of QSAR models of aquatic toxicity for the training set. The internal prediction accuracy for the modeling set ranged from 0.76 to 0.93 as measured by the leave-one-out cross-validation correlation coefficient ( Q abs2). The prediction accuracy for the external validation sets I and II ranged from 0.71 to 0.85 (linear regression coefficient R absI2) and from 0.38 to 0.83 (linear regression coefficient R absII2), respectively. The use of an applicability domain threshold implemented in most models generally improved the external prediction accuracy but at the same time led to a decrease in chemical space coverage. Finally, several consensus models were developed by averaging the predicted aquatic toxicity for every compound using all 15 models, with or without taking into account their respective applicability domains. We find that consensus models afford higher prediction accuracy for the external validation data sets with the highest space coverage as compared to individual constituent models. Our studies prove the power of a collaborative and consensual approach to QSAR model development. The best validated models of aquatic toxicity developed by our collaboratory (both individual and consensus) can be used as reliable computational predictors of aquatic toxicity and are available from any of the participating laboratories." @default.
• W2157851318 created "2016-06-24" @default.
• W2157851318 creator A5022850021 @default.
• W2157851318 creator A5026329292 @default.
• W2157851318 creator A5037756450 @default.
• W2157851318 creator A5051300692 @default.
• W2157851318 creator A5055688208 @default.
• W2157851318 creator A5067679577 @default.
• W2157851318 creator A5070041767 @default.
• W2157851318 creator A5070580886 @default.
• W2157851318 creator A5072029339 @default.
• W2157851318 creator A5078536199 @default.
• W2157851318 date "2008-03-01" @default.
• W2157851318 modified "2023-10-16" @default.
• W2157851318 title "Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis" @default.
• W2157851318 cites W1496663395 @default.
• W2157851318 cites W1504991194 @default.
• W2157851318 cites W1545231783 @default.
• W2157851318 cites W1570912112 @default.
• W2157851318 cites W1571439140 @default.
• W2157851318 cites W1963790256 @default.
• W2157851318 cites W1968756812 @default.
• W2157851318 cites W1972156862 @default.
• W2157851318 cites W1978239142 @default.
• W2157851318 cites W1979213306 @default.
• W2157851318 cites W1986416602 @default.
• W2157851318 cites W1989260418 @default.
• W2157851318 cites W1990768268 @default.
• W2157851318 cites W1993452491 @default.
• W2157851318 cites W1994161110 @default.
• W2157851318 cites W2002503643 @default.
• W2157851318 cites W2006360003 @default.
• W2157851318 cites W2010611103 @default.
• W2157851318 cites W2015870870 @default.
• W2157851318 cites W2017547564 @default.
• W2157851318 cites W2022400681 @default.
• W2157851318 cites W2031560630 @default.
• W2157851318 cites W2039340637 @default.
• W2157851318 cites W2040176199 @default.
• W2157851318 cites W2044253756 @default.
• W2157851318 cites W2047399377 @default.
• W2157851318 cites W2054716083 @default.
• W2157851318 cites W2057433555 @default.
• W2157851318 cites W2059713851 @default.
• W2157851318 cites W2061139820 @default.
• W2157851318 cites W2062427002 @default.
• W2157851318 cites W2068950612 @default.
• W2157851318 cites W2069499971 @default.
• W2157851318 cites W2070955875 @default.
• W2157851318 cites W2071551353 @default.
• W2157851318 cites W2073503722 @default.
• W2157851318 cites W2077156091 @default.
• W2157851318 cites W2077582053 @default.
• W2157851318 cites W2084661650 @default.
• W2157851318 cites W2086190989 @default.
• W2157851318 cites W2087661061 @default.
• W2157851318 cites W2099538400 @default.
• W2157851318 cites W2104676838 @default.
• W2157851318 cites W2134898582 @default.
• W2157851318 cites W2135897723 @default.
• W2157851318 cites W2136995501 @default.
• W2157851318 cites W2138092501 @default.
• W2157851318 cites W2138188160 @default.
• W2157851318 cites W2140489263 @default.
• W2157851318 cites W2160101329 @default.
• W2157851318 cites W2173710522 @default.
• W2157851318 cites W2210079610 @default.
• W2157851318 cites W2216412596 @default.
• W2157851318 cites W2218897511 @default.
• W2157851318 cites W28125880 @default.
• W2157851318 cites W4211021846 @default.
• W2157851318 cites W4230674625 @default.
• W2157851318 doi "https://doi.org/10.1021/ci700443v" @default.
• W2157851318 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18311912" @default.
• W2157851318 hasPublicationYear "2008" @default.
• W2157851318 type Work @default.
• W2157851318 sameAs 2157851318 @default.
• W2157851318 citedByCount "261" @default.
• W2157851318 countsByYear W21578513182012 @default.
• W2157851318 countsByYear W21578513182013 @default.
• W2157851318 countsByYear W21578513182014 @default.
• W2157851318 countsByYear W21578513182015 @default.
• W2157851318 countsByYear W21578513182016 @default.
• W2157851318 countsByYear W21578513182017 @default.
• W2157851318 countsByYear W21578513182018 @default.
• W2157851318 countsByYear W21578513182019 @default.
• W2157851318 countsByYear W21578513182020 @default.
• W2157851318 countsByYear W21578513182021 @default.
• W2157851318 countsByYear W21578513182022 @default.
• W2157851318 countsByYear W21578513182023 @default.
• W2157851318 crossrefType "journal-article" @default.
• W2157851318 hasAuthorship W2157851318A5022850021 @default.
• W2157851318 hasAuthorship W2157851318A5026329292 @default.
• W2157851318 hasAuthorship W2157851318A5037756450 @default.
• W2157851318 hasAuthorship W2157851318A5051300692 @default.
• W2157851318 hasAuthorship W2157851318A5055688208 @default.
• W2157851318 hasAuthorship W2157851318A5067679577 @default.
• W2157851318 hasAuthorship W2157851318A5070041767 @default.

• next