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. 2015 Nov 24;2:150065.
doi: 10.1038/sdata.2015.65.

VenomKB, a New Knowledge Base for Facilitating the Validation of Putative Venom Therapies

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Free PMC article

VenomKB, a New Knowledge Base for Facilitating the Validation of Putative Venom Therapies

Joseph D Romano et al. Sci Data. .
Free PMC article

Abstract

Animal venoms have been used for therapeutic purposes since the dawn of recorded history. Only a small fraction, however, have been tested for pharmaceutical utility. Modern computational methods enable the systematic exploration of novel therapeutic uses for venom compounds. Unfortunately, there is currently no comprehensive resource describing the clinical effects of venoms to support this computational analysis. We present VenomKB, a new publicly accessible knowledge base and website that aims to act as a repository for emerging and putative venom therapies. Presently, it consists of three database tables: (1) Manually curated records of putative venom therapies supported by scientific literature, (2) automatically parsed MEDLINE articles describing compounds that may be venom derived, and their effects on the human body, and (3) automatically retrieved records from the new Semantic Medline resource that describe the effects of venom compounds on mammalian anatomy. Data from VenomKB may be selectively retrieved in a variety of popular data formats, are open-source, and will be continually updated as venom therapies become better understood.

Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Schematic overview of building VenomKB.
MeSH was used to identify a core set of relevant articles, which were then passed to three methods of knowledge extraction (manual review, the VExtractor algorithm, and the SemanticVExtractor algorithm). The outputs of these three methods were then collected and assembled as VenomKB.
Figure 2
Figure 2. Screenshot of VenomKB’s knowledge base browsing interface.
Image shows the first 8 records of the ‘Manually Curated Venoms’ table. The top bar has links to the knowledge base home page and each of the three current database tables. Search filters are in the frame entitled ‘Filters’ on the right side of the interface. Download links (for CSV, XML, and JSON format) and pagination functionality are located at the bottom of the page, out of range of the screenshot.
Figure 3
Figure 3. The top 10 most frequent UMLS semantic types represented in the SemanticVExtractor data output, graphed by total counts.
Shown separately are counts for compound semantic types, object semantic types, and the sum of both, each plotted in separate colors as indicated by the figure legend. The x-axis lists each of the top 10 UMLS semantic types by their 4-letter abbreviation, for ease of plotting. Each abbreviation is defined beneath the plot, in descending order of frequency.

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References

Data Citations

    1. Romano J. D., Tatonetti N. P.. Figshare. 2015 http://dx.doi.org/10.6084/m9.figshare.1287000 - DOI
    1. Romano J. D., Tatonetti N. P.. Figshare. 2015 http://dx.doi.org/10.6084/m9.figshare.1286999 - DOI
    1. Romano J. D., Tatonetti N. P.. Figshare. 2015 http://dx.doi.org/10.6084/m9.figshare.1287001 - DOI
    1. Romano J. D., Tatonetti N. P.. Figshare. 2015 http://dx.doi.org/10.6084/m9.figshare.1289881 - DOI

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