Article

ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format

BMC Biotechnology (Impact Factor: 2.59). 01/2013; 13(1):2. DOI: 10.1186/1472-6750-13-2
Source: PubMed

ABSTRACT 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.

Results
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.

Conclusion
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.

Download full-text

Full-text

Available from: Nathan Andrew Baker, Jul 29, 2015
1 Follower
 · 
159 Views
  • Source
    • "(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). "
    [Show abstract] [Hide abstract]
    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.
    Particuology 06/2015; 21:1-19. DOI:10.1016/j.partic.2014.12.001 · 1.65 Impact Factor
  • Source
    • "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. "
    [Show abstract] [Hide abstract]
    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.
    Journal of Nanoparticle Research 02/2014; 16(2). DOI:10.1007/s11051-014-2282-9 · 2.28 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: The quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. Data will not be translated to knowledge. At worst, erroneous conclusions will be drawn and future research may be misdirected. Nanoinformatics can be a powerful approach to enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. In 2012, the nanoinformatics community believed it was important to critically evaluate and refine currently available nanoinformatics approaches in order to best inform the science and support the future of predictive nanotechnology. The Greener Nano 2012: Nanoinformatics Tools and Resources Workshop brought together informatics groups with materials scientists active in nanoscience research to evaluate and reflect on the tools and resources that have recently emerged in support of predictive nanotechnology. The workshop goals were to establish a better understanding of current nanoinformatics approaches and to clearly define immediate and projected informatics infrastructure needs of the nanotechnology community. The theme of nanotechnology environmental health and safety (nanoEHS) was used to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. The benefit here is that the same properties that impact the performance of products could also be the properties that inform EHS. From a decision management standpoint, the dual use of such data should be considered a priority. Key outcomes include a proposed collaborative framework for data collection, data sharing and information integration.
    Computational Science & Discovery 01/2013; 6(1):14008. DOI:10.1088/1749-4699/6/1/014008
Show more