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An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology

Robinson, RLM and Cronin, MTD and Richarz, A-N and Rallo, R (2015) An ISA-TAB-Nano based data collection framework to support data-driven modelling of nanotoxicology. BEILSTEIN JOURNAL OF NANOTECHNOLOGY, 6. pp. 1978-1999. ISSN 2190-4286

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Abstract

Analysis of trends in nanotoxicology data and the development of data driven models for nanotoxicity is facilitated by the reporting of data using a standardised electronic format. ISA-TAB-Nano has been proposed as such a format. However, in order to build useful datasets according to this format, a variety of issues has to be addressed. These issues include questions regarding exactly which (meta)data to report and how to report them. The current article discusses some of the challenges associated with the use of ISA-TAB-Nano and presents a set of resources designed to facilitate the manual creation of ISA-TAB-Nano datasets from the nanotoxicology literature. These resources were developed within the context of the NanoPUZZLES EU project and include data collection templates, corresponding business rules that extend the generic ISA-TAB-Nano specification as well as Python code to facilitate parsing and integration of these datasets within other nanoinformatics resources. The use of these resources is illustrated by a “Toy Dataset” presented in the Supporting Information. The strengths and weaknesses of the resources are discussed along with possible future developments.

Item Type: Article
Uncontrolled Keywords: Science & Technology; Technology; Physical Sciences; Nanoscience & Nanotechnology; Materials Science, Multidisciplinary; Physics, Applied; Science & Technology - Other Topics; Materials Science; Physics; databases; ISA-TAB-Nano; nanoinformatics; nanotoxicology; quantitative structure-activity relationship (QSAR); METAL-OXIDE NANOPARTICLES; ESCHERICHIA-COLI; ENGINEERED NANOMATERIALS; ELECTRON-MICROSCOPY; SIO2 NANOPARTICLES; OPTIMAL DESCRIPTOR; RISK-ASSESSMENT; ECLECTIC DATA; QSAR MODEL; CYTOTOXICITY
Subjects: Q Science > QD Chemistry
R Medicine > RA Public aspects of medicine > RA1190 Toxicology. Poisions
Divisions: Pharmacy & Biomolecular Sciences
Publisher: BEILSTEIN-INSTITUT
Related URLs:
Date Deposited: 09 Feb 2016 10:57
Last Modified: 09 Feb 2016 10:57
DOI or Identification number: 10.3762/bjnano.6.202
URI: http://researchonline.ljmu.ac.uk/id/eprint/2877

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