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See also Data science portal | Google scholar | PubMed Alternative Interfaces | PubReMiner | Semantic search | Web 2.0

"...GoPubMed® allows users to find information significantly faster and guarantees completeness of search results. The fundamental difference between GoPubMed’s® semantic search technology and traditional search engines such as PubMed or Google is the use of background knowledge. Semantic algorithms connect text – abstracts from the MEDLINE database – to background knowledge in the form of semantic networks of concept categories, also called ontologies or knowledge base. This is done by meaning and not by keywords only. So results are meaningfully structured and intelligent semantic navigation becomes possible. The concept categories come from the Gene Ontology (GO), the Medical Subject Headings (MeSH), the Universal Protein Resource (UniProt), Authors, Locations, Journals, and Publication Dates. In GoPubMed® the user does the ranking. Examples below clearly demonstrate this semantic power...." (see Help)

GoPubMed is a knowledge-based semantic browsing tool for the life sciences. GoPubMed searches all citations in PubMed for occurrences of a disease, compound name, or gene, and displays / categorizes results to help you visualize major biomedical concepts for the query. Its statistical features show you how your topic is trending such as top authors, publications over time, and a world map showing where publications originate. The Gene Ontology (GO) and Medical Subject Headings (MeSH) serve as a "Table of contents" to structure articles in the display. The search engine allows users to find relevant results in biomedical texts faster than through PubMed alone. The technology used in GoPubMed is applied to texts in order to mine them. Developed at the Technical University of Dresden by Michael Schroeder and Transinsight, GoPubMed has been called one of the first web 2.0 and semantic search engines.

What GoPubMed does to expand a search query is add 'ontologies' or categories to how articles are displayed. As mentioned, the Medical Subject Headings (MeSH) and the Gene Ontology (GO) are used by GoPubMed to identify the interrelatedness of articles. The statistics feature is a semanto-bibliometric analysis of search results. After conducting your search, see the “Statistics” tab to view bar graphs, charts and visual representations of top authors, top countries, top cities, top journals, and so on.

Sorting results

Results in GoPubMed can be filtered by:

  • “what” – which contains the terms and knowledge base concepts related to your query
  • “who” – authors contributing to the articles
  • “where” – where the authors and institutions for the article are located, as well as a limit to specific journals or high impact factor journals as a group and
  • “when” – the year the articles were published.

Alternative, data-mining tools


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