Informatics and standards for nanomedicine technology

Knowledge Discovery and Informatics Group, Pacific Northwest National Laboratory, Richland, WA, USA.
Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology (Impact Factor: 4.49). 09/2011; 3(5). DOI: 10.1002/wnan.152
Source: PubMed


There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration; data sharing; unambiguous representation and interpretation of data; semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this article, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, because of gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret, and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, and so on. Progress toward resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this article will be essential to the rapidly growing field of nanomedicine informatics. WIREs Nanomed Nanobiotechnol 2011 DOI: 10.1002/wnan.152 This article is a U.S. Government work, and as such, is in the public domain in the United States of America. For further resources related to this article, please visit the WIREs website.

1 Follower
55 Reads
  • Source
    • "Different types of information are stored in the database: particles' size, size distribution, zeta potential, aggregation properties, purity, etc. Importantly, a great importance is given for (i) quality control of data before their actual integration to the repository, (ii) consistency of MNPs' naming and description ontology, (iii) storing protocols for enabling proper data sharing according to Nano-Tab (D. G. Thomas, Pappu, and Baker 2011; D. G. Thomas et al. 2011) recommendations. "
    [Show abstract] [Hide abstract]
    ABSTRACT: In this chapter, we discuss the application of modern cheminformatics approaches such as Quantitative Structure – Activity Relationships (QSAR) modeling towards developing computational tools capable of forecasting the biological effects of Manufactured NanoParticles (MNPs) solely from the knowledge of their physical, chemical, and geometrical properties; by analogy with QSAR we term such approach Quantitative Nanostructure – Activity Relationships (QNAR) modelling. First, we stress the difficulties of compiling, curating, and integrating experimental MNP related data from different sources. We illustrate those difficulties with the case study of automatic and manual literature mining for CeO2 nanoparticles. Second, we discuss the major approaches for QNAR model building and validation using both experimental and computed properties of nanomaterials. We consider two different categories of MNP datasets: (i) those comprising MNPs with diverse metal cores and different surface-modifying organic molecules for which experimentally measured properties can be used as MNP descriptors in building QNAR models, and (ii) those involving MNPs possessing the same core but different surface-modifying organic molecules, where in the first approximation the differences can be only correlated with differences in the structure of the decorating surface modifiers. In this case, chemical descriptors can be calculated for a single representative of the decorative molecule and used in QSAR modeling. Recent studies reporting on QNAR models are recapitulated. Overall, we show how QNAR modeling can be useful for (i) predicting activity profiles of novel MNPs solely from their representative descriptors and (ii) designing and manufacturing safer nanomaterials with desired properties.
    Nanotoxicology: Progress toward Nanomedicine, 2nd edited by Nancy A. Monteiro-Riviere, C. Lang Tran, 03/2014; CRC Press., ISBN: 9781482203875
  • Source
    • "The use of novel, “visual” nano-ontologies could provide greater semantic content, together with research on more advanced methods of text mining from the literature. As mentioned, the choice of unique material identifiers is an important subtopic of ongoing research by the new Nanomaterials Registry supported jointly by the NCI, the National Institute of Environmental Health Sciences, and the National Institute of Biomedical Imaging and Bioengineering.70 The registry has developed a prototype database and user interface and initial datasets are being curated.71 "
    [Show abstract] [Hide abstract]
    ABSTRACT: Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and -omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings.
    International Journal of Nanomedicine 07/2012; 7:3867-90. DOI:10.2147/IJN.S24582 · 4.38 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: With the increasing use of nanoparticles in food processing, filtration/purification and consumer products, as well as the huge potential of their use in nanomedicine, a quantitative understanding of the effects of nanoparticle uptake and transport is needed. We provide examples of novel methods for modeling complex bio-nano interactions which are based on stochastic process algebras. Since model construction presumes sufficient availability of experimental data, recent developments in "nanoinformatics", an emerging discipline analogous to bioinfomatics, in building an accessible information infrastructure are subsequently discussed. Both computational areas offer opportunities for Filipinos to engage in collaborative, cutting edge research in this impactful field.
    01/2012; 17:114-121. DOI:10.1142/S2010194512008008
Show more

Full-text (2 Sources)

55 Reads
Available from
May 21, 2014