What is knowledge-based search?
Knowledge-based search helps you find the answers to your question faster. By using a domain ontology as structured background knowledge, the search results are sorted into meaningful categories. You can use these categories to narrow your set of found articles to the relevant ones. In many cases the categories will already represent the answer to your question.
How does it help finding answers?
See the following question: Which biological process is the protein rab5 involved in and where is it located in the cell? Type “rab5″ and wait for the tree on the left to appear. Have a look at the knowledge base. A click on “biological_process” shows endocytosis, and clicking on “cellular component” shows endosome as answers for this question.
What is the Gene Ontology (GO)?
The GO provides a controlled vocabulary to describe gene and gene products in different organisms. GO is a knowledge network containing about 20,000 biological terms. It is built up as a directed acyclic graph starting from three basic areas:
- the molecular function of gene products
- their role in multi-step biological processes
- their localization to cellular components
GO terms are classified into only one of the three branches of the ontology. Although the ontology is presented as a tree, it is a network with cross links, so it is possible to navigate to a term of interest on different paths. Therefore, a term of interest can be reached from quite different points of view. See http://www.geneontology.org/ for more details about Gene Ontology.
What are the Medical Subject Headings (MeSH)?
MeSH is the controlled vocabulary thesaurus from the National Library of Medicine. It consists of sets of terms in a hierarchical structure that permits searching at various levels of specificity. At the top level of the hierarchy are very general headings such as “Anatomy” or “Diseases”. More specific headings are found at narrower levels. There are more than 110,000 MeSH concepts in GoPubMed®. There are also thousands of cross-references that assist in finding the most appropriate MeSH concept, so it is possible to navigate to a term of interest on different paths. Therefore, a term of interest can be reached from quite different points of view. From the eleven levels of the MeSH hierarchy, GoPubMed® uses the following parts:
- Biological Sciences
- Chemicals and Drugs
- Health Care
- Named Groups
- Natural Sciences
- Psychiatry and Psychology
- Techniques and Equipment
- Technology, Industry, Agriculture
How can I export the results?
You can export a single article or the first 100 articles. To export only one article, click on the export icon symbol to the left of the article , which opens a menu with the available formats: RDF, Plain Text, XML, BibTeX, EndNote/Citavi, Refworks, and PubMed IDs. To the top right of the articles you will find the export icon for the first 100 articles. Simply click on it and choose “Save link as …”.
Do you provide GoPubMed® in languages other than English?
At the moment GoPubMed® is only available in English. Most abstracts in PubMed are written in English. The best available background knowledge is provided in this language. If you are really keen on using GoPubMed® in other languages, please send us feedback: email@example.com
How can I find the full article?
Full articles can be found using the query Fulltext[journal] or clicking on “Free full text only”. The link “Read Full Text” goes to the article on the journal’s own web site where some items are available free of charge and others require a subscription.
How can I switch off abstracts?
To view only the titles without the full abstract, click on the symbol on the left side of the summary title , which hides the full abstract of all articles. To switch on and off the abstract of one article, click on the same symbol to the left of the article.
Where is the clipboard?
You can find the clipboard under “My Search” on the left side. To move articles in and out, click on or next to the article. The clipboard is stored as long as your browser session lasts.
What are the Statistics?
With Statistics we perform bibliometric analyses of search results. The results are shown through bar graphs, charts, and visual representations of the top authors, top countries, top cities, top journals, number of publications over time, and author collaboration network. You can reach the Statistics by clicking on .
Our promise: Any information submitted by users to GoPubMed® is stored for internal use only. None of this information will be shared with third parties without your permission.
The hierarchical organization of retrieved information is done with Transinsight’s Enterprise Semantic Intelligence® Platform. Users can edit and update authors’ profiles. Users can contact authors via GoPubMed®. All information is used only internally and no data are or will be given to third party.
Various German sponsors contributed to GoPubMed®, namely the German Federal Ministry for Economy and the Ministry for Education and Research. The Techniche Universität Dresden and Transinsight also contribute significantly to the freely available service over the last 10 years (as of November 12, 2013).
Running a semantic search engine is expensive and requires about ten times the computing power of an ordinary keyword search engine. The energy consumption is therefore higher. Providing the service for free is a strong effort of the Techniche Universität Dresden and Transinsight. Improving the service at least twice a year requires a strong financial background. Therefore we highly appreciate any donation to make the service better day by day. Donate via PayPal here.
The Product Enterprise Semantic Intelligence Platform
GoPubMed® is based on Transinsight’s Enterprise Semantic Intelligence® Platform. These products contain many more advanced features than shown in GoPubMed®. Ontology- Background-Knowledge editing and semi-automated ontology- and definition-generation are two of those features. To find out more about ESI® please visit www.Transinsight.com/products.
GoPubMed® is originaly based on this publication:
Andreas Doms and Michael Schroeder, “GoPubMed: Exploring PubMed with the GeneOntology”, Nucleic Acid Research, 33 (Web Server Issue): W783–W786, 2005