Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Richard Sherhod"'
Autor:
Lilia Fisk, Valerie J. Gillet, William C. Drewe, Mukesh Patel, Jonathan D. Vessey, Steven J. Canipa, Laurence Coquin, Richard Sherhod, Jeffrey Plante
Publikováno v:
Toxicology Research. 4:46-56
Emerging pattern mining techniques have been applied to datasets of Ames mutagens. The discovered patterns give rise to clusters of compounds from large and biased datasets which are used to develop new structural alerts for mutagenicity in the Derek
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cebc49df912ce02f0bcbd51dac353a29
https://doi.org/10.1039/c4tx00071d
https://doi.org/10.1039/c4tx00071d
Publikováno v:
Journal of Chemical Information and Modeling. 52:3074-3087
The design of new alerts, that is, collections of structural features observed to result in toxicological activity, can be a slow process and may require significant input from toxicology and chemistry experts. A method has therefore been developed t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d37fa8106f6c1997836c1e7fc93ba79
https://doi.org/10.1021/ci300254w
https://doi.org/10.1021/ci300254w
Autor:
Steven J. Enoch, Claire M. Ellison, Richard Sherhod, Judith C. Madden, Mark T. D. Cronin, Philip N. Judson
Publikováno v:
Journal of Chemical Information and Modeling. 51:975-985
It is important that in silico models for use in chemical safety legislation, such as REACH, are compliant with the OECD Principles for the Validation of (Q)SARs. Structural alert models can be useful under these circumstances but lack an adequately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d1adacc46b2bd1860b91de96f6e130b0
https://doi.org/10.1021/ci1000967
https://doi.org/10.1021/ci1000967
Autor:
Richard, Sherhod, Philip N, Judson, Thierry, Hanser, Jonathan D, Vessey, Samuel J, Webb, Valerie J, Gillet
Publikováno v:
Journal of chemical information and modeling. 54(7)
Knowledge-based systems for toxicity prediction are typically based on rules, known as structural alerts, that describe relationships between structural features and different toxic effects. The identification of structural features associated with t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::377dc61a9264bffaf9d089e377f5a3e3
https://pubmed.ncbi.nlm.nih.gov/24873983
https://pubmed.ncbi.nlm.nih.gov/24873983
Publikováno v:
Journal of Cheminformatics
Predicting the risk of toxic and environmental effects of chemical compounds is of great importance to all chemical industries [1]. Expert systems have shown success in predicting toxic risk by applying established knowledge of toxicology encoded as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::850ca2f0b721f4ba257a4785bb13645e
https://doi.org/10.1186/1758-2946-5-s1-o9
https://doi.org/10.1186/1758-2946-5-s1-o9