ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format
(Impact Factor: 2.03).
01/2013; 13(1):2. DOI: 10.1186/1472-6750-13-2
Background and motivation
The high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Specifically, in its current state, data cannot be effectively utilized for the development of predictive models that will inform the rational design of nanomaterials.
We have developed a specification called ISA-TAB-Nano, which comprises four spreadsheet-based file formats for representing and integrating various types of nanomaterial data. Three file formats (Investigation, Study, and Assay files) have been adapted from the established ISA-TAB specification; while the Material file format was developed de novo to more readily describe the complexity of nanomaterials and associated small molecules. In this paper, we have discussed the main features of each file format and how to use them for sharing nanomaterial descriptions and assay metadata.
The ISA-TAB-Nano file formats provide a general and flexible framework to record and integrate nanomaterial descriptions, assay data (metadata and endpoint measurements) and protocol information. Like ISA-TAB, ISA-TAB-Nano supports the use of ontology terms to promote standardized descriptions and to facilitate search and integration of the data. The ISA-TAB-Nano specification has been submitted as an ASTM work item to obtain community feedback and to provide a nanotechnology data-sharing standard for public development and adoption.
Figures in this publication
Available from: Terence Arthur Wilkins
- "(For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.) Table 6 ISA-TAB-NANO file types (Thomas et al., 2013). "
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ABSTRACT: There is increasing recognition that some nanomaterials may pose a risk to human health and the environment. Moreover, the industrial use of the novel engineered nanomaterials (ENMs) increases at a higher rate than data generation for hazard assessment; consequently, many of them remain untested. The large number of nanomaterials and their variants (e.g., different sizes and coatings) requiring testing and the ethical pressure towards nonanimal testing means that in a first instance, expensive animal bioassays are precluded, and the use of (quantitative) structure–activity relationships ((Q)SARs) models as an alternative source of (screening) hazard information should be explored. (Q)SAR modelling can be applied to contribute towards filling important knowledge gaps by making best use of existing data, prioritizing the physicochemical parameters driving toxicity, and providing practical solutions for the risk assessment problems caused by the diversity of ENMs. This paper covers the core components required for successful application of (Q)SAR methods to ENM toxicity prediction, summarizes the published nano-(Q)SAR studies, and outlines the challenges ahead for nano-(Q)SAR modelling. It provides a critical review of (1) the present availability of ENM characterization/toxicity data, (2) the characterization of nanostructures that meet the requirements for (Q)SAR analysis, (3) published nano-(Q)SAR studies and their limitations, (4) in silico tools for (Q)SAR screening of nanotoxicity, and (5) prospective directions for the development of nano-(Q)SAR models.
Available from: Olena Mokshyna
- "A standardised data exchange format to share data and a unified ontology for data collection is needed to ensure a certain quality standard in terms of completeness, avoid duplication, allow a comparison between data from different sources and make it possible to integrate different datasets into one database. ISA-TAB-nano (Thomas et al., 2013) has been identified as a suitable standard format, defining a set of linked spreadsheet files (Investigation, Study, Assay and Material), with a pre-defined file structure and syntax for (meta)data. Furthermore, the quality and suitability of the data for developing predictive toxicology models are being assessed. "
Available from: Alla Toropova
- "The representation of nanomaterials in standardized form is an object of research work (Thomas et al. 2013). However, most probably, the standardization will give clear transparent results (databases) in the future. "
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ABSTRACT: The possibility of building up predictive model for cytotoxicity of SiO2-nanoparticles (SiO2-NPs) by means of so-called optimal descriptors which are mathematical functions of size and concentration of SiO2-NPs is demonstrated with data on sixteen systems’ “size–concentration.” The calculation has been carried out by means of the CORAL software (http://www.insilico.eu/coral/). The statistical quality of the best model for the cytotoxic inhibition ratio (%) of human lung fibroblasts cultured in the media containing different concentrations of SiO2‐NPs which is measured by MTT assay is the following: n = 10, r 2 = 0.9837, s = 2.53 %, F = 483 (training set) and n = 6, r 2 = 0.9269, s = 7.94 % (test set). The perspectives of this approach are discussed.
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