Details

Autor(en) / Beteiligte

• Avancini, Daniele
• Menzies, Georgina E
• Morgan, Claire
• Wills, John
• Johnson, George E
• White, Paul A
• Lewis, Paul D

Titel

MutAIT: an online genetic toxicology data portal and analysis tools

Ist Teil von

• Mutagenesis, 2016-05, Vol.31 (3), p.323-328

Ort / Verlag

England

Erscheinungsjahr

2016

Quelle

Oxford Journals 2020 Medicine

Beschreibungen/Notizen

• Assessment of genetic toxicity and/or carcinogenic activity is an essential element of chemical screening programs employed to protect human health. Dose-response and gene mutation data are frequently analysed by industry, academia and governmental agencies for regulatory evaluations and decision making. Over the years, a number of efforts at different institutions have led to the creation and curation of databases to house genetic toxicology data, largely, with the aim of providing public access to facilitate research and regulatory assessments. This article provides a brief introduction to a new genetic toxicology portal called Mutation Analysis Informatics Tools (MutAIT) (www.mutait.org) that provides easy access to two of the largest genetic toxicology databases, the Mammalian Gene Mutation Database (MGMD) and TransgenicDB. TransgenicDB is a comprehensive collection of transgenic rodent mutation data initially compiled and collated by Health Canada. The updated MGMD contains approximately 50 000 individual mutation spectral records from the published literature. The portal not only gives access to an enormous quantity of genetic toxicology data, but also provides statistical tools for dose-response analysis and calculation of benchmark dose. Two important R packages for dose-response analysis are provided as web-distributed applications with user-friendly graphical interfaces. The 'drsmooth' package performs dose-response shape analysis and determines various points of departure (PoD) metrics and the 'PROAST' package provides algorithms for dose-response modelling. The MutAIT statistical tools, which are currently being enhanced, provide users with an efficient and comprehensive platform to conduct quantitative dose-response analyses and determine PoD values that can then be used to calculate human exposure limits or margins of exposure.