GoPubMed
GoPubMed is a knowledge-based search engine for biomedical texts. The system is designed to enhance the efficiency of retrieving specific information from scientific literature in the PubMed database, which is maintained by the National Center for Biotechnology Information (NCBI). GoPubMed was developed by the Transinsight, a German bioinformatics company, in collaboration with the Technical University of Dresden and the University of Dresden.
Overview[edit | edit source]
GoPubMed utilizes the Gene Ontology (GO) and Medical Subject Headings (MeSH) for sorting and filtering search results. The search engine works by applying a two-step process: retrieval and refinement. In the retrieval phase, GoPubMed identifies relevant articles from the PubMed database. In the refinement phase, the system categorizes the retrieved articles based on the GO and MeSH terms, allowing users to narrow down the search results.
Features[edit | edit source]
GoPubMed offers several features that distinguish it from other biomedical search engines. These include:
- Term Clouds: GoPubMed provides a visual representation of the most relevant terms in the search results. This feature helps users to quickly identify the main topics related to their search query.
- Term Navigation: Users can navigate through the search results by clicking on the terms in the term cloud or the term tree. This feature allows users to explore related topics without having to perform additional searches.
- Term Details: For each term, GoPubMed provides a detailed description, including its definition, synonyms, and related terms. This feature helps users to understand the context of the terms in the search results.
- Article Preview: GoPubMed provides a preview of the abstracts of the articles in the search results. This feature allows users to assess the relevance of the articles without having to open them.
Applications[edit | edit source]
GoPubMed can be used in various fields of biomedical research, including genomics, proteomics, metabolomics, and pharmacogenomics. The system can also be used in clinical research for literature review, hypothesis generation, and data interpretation.
See Also[edit | edit source]
References[edit | edit source]
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Contributors: Prab R. Tumpati, MD
