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TYPE 1: extract relationships and allow for 1) graphical visualization or navigation; or 2) refining queries
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AliBaba [15]
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http://alibaba.informatik.hu-berlin.de/
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Extract relationships between biological objects and map them into a graphical network
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BioIE [16]
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http://umber.sbs.man.ac.uk/dbbrowser/bioie/
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Extract informative sentences from retrieved results
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Chilibot [17]
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http://www.chilibot.net/
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Extract biological relationships from search results
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ConceptLink [18]
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http://project.cis.drexel.edu/conceptlink
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Extract relationships between medical concepts and allow graphical visualization
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PubNet [29]
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http://pubnet.gersteinlab.org/
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Extract several relationships from the search results and then map them into networks
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XplorMed [20]
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http://www.bork.embl-heidelberg.de/xplormed/
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Extract dependency relations among words and allow users to refine queries using these words
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TYPE 2: organize results by ontologies or hierarchies
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GoPubMed [21]
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http://www.gopubmed.org/
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Sort PubMed query results through Gene Ontology and MeSH hierarchy
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MEVA [22]
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http://www.med-ai.com/meva/index.html
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Summarize search results according to MeSH hierarchy
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FABLE [23]
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http://fable.chop.edu/
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Tag gene and protein occurrences in text
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PubReMiner [24]
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http://bioinfo.amc.uva.nl/human-genetics/pubreminer/
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Categories include words, MeSH, authors, journals, year, substances and country
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PubMed Assistant [25]
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http://metnet.vrac.iastate.edu/browser/
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Lists MeSH and chemicals, with link-outs to PubMed, Google and Google Scholar
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TYPE 3: cluster articles into categories
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Vivísimo ClusterMed [26]
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http://clustermed.info/
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Cluster articles into several categories
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HubMed [27]
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http://www.hubmed.org
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Cluster related articles and allow for graphical visualization
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TYPE 4: rank articles
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PubFocus [28]
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http://www.pubfocus.com/
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Rank articles by the journal impact factor and volume of forward references
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ReleMed [29]
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http://www.relemed.com/
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Rank articles by relevance
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