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  • Framework for Intelligent Nano Discovery (FiND)
    • Description: Computers are essential to research yet the different ways in which computers can automate or speed up research have not been explored fully. Researchers are publishing their experimental results faster than ever before and the number of articles to read on a single subject now presents an overwhelming task. This project (FiND) aims to expedite this process through an extensible backbone infrastructure that includes a Web User Interface, Perl Core and MySQL Database. All while utilizing scripting and programming language constraints Perl, HTML, CSS, CGI and MySQL. This project attempts to simplify this process by reducing time spent in exhaustive article researching and allow researchers to spend it perusing deeper in the article contents not to mention a filtration system to determine whether an article is of interest.
    • Download : GitHUB
  • Nano Entity Recognition & Discovery (NERD)
    • Description: Extracting information, such as extracting relationships between specific types of entities, or inferring facts first requires that the mentions of the entities in the text be detected.  Several chemical entity extractors have been developed however these NERs identify chemical names, chemical elements, chemical formulas, chemical prefixes, reaction names, enzymes, amino acids, and amino acid sequences.  However, additional context, such as the role of the chemical in the reaction, is not included. NERD extracts entities characterizing the synthesis conditions needed to generate nanoparticles with desired physico-chemical and biological characteristics.
    • Download: GitHUB



  • Engineered Nano Database (END) Corpus
    • Description: The END corpus currently contains ~26,000 annotated terms present within drug product labels for 41 nanomedicines that are approved for clinical use by the U.S. Food and Drug Administration (FDA).  The labels were obtained from the Drugs@FDA online database and are freely accessible.
    • Download: Coming Soon
    • Citation: An annotated corpus with nanomedicine and pharmacokinetic parameters. Nastassja Lewinski, Ivan Jimeniz and Bridget McInnes. Journal of Nanomedicine, 2017 (in press).
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