MEDIE is an intelligent search engine to retrieve biomedical correlations from MEDLINE,
based on indexing by Natural Language Processing and Text Mining techniques.
You can find abstracts/sentences in MEDLINE by specifying semantics of correlations;
for example, "What
activates p53" and "What causes colon cancer".
Semantic search is to use a semantic query for finding
biomedical correlations. Input a subject, a verb, and an
object of a concept (or either of them) into a form. Results
of the query will be shown in a second.
Examples:
A GCL query is directly passed to a GCL server. See the following table for the details of GCL. If you want to see
examples of GCL queries, just click "Show query" in the search summary of semantic/keyword search, and you will see a GCL
query submitted to a server.
The customization of the number of results is available as in Semantic Search.
A list of GCL operators:
| [tag] | Region covered with "<tag>" |
| A > B | A containing B |
| A < B | A contained by B |
| A - B | Starting with A and ending with B |
| A & B | A and B |
| A | B | A or B |
| $X | Variable (used only in attribute values) |
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This system is provided by the Tsujii Laboratory "AS IS" without warranty of any kind. We may modify or halt this
system at any time without prior notification.
This system is built on the Medline database leased from the National Library of Medicine [NLM].
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NLM represents that its data were formulated with a reasonable
standard of care. Except for this representation, NLM makes no
representation or warranties, expressed or implied. This includes, but
is not limited to, any implied warranty of merchantability or fitness
for a particular purpose, with respect to the NLM data, and NLM
specifically disclaims any such warranties and representations.
All complete or parts of U.S. National Library of Medicine (NLM)
records that are redistributed or retransmitted must be identified as
being derived from NLM data.
NLM data are produced by a U.S. Government agency and include works
of the United States Government that are not protected by U.S.
copyright law but may be protected by non-US copyright law, as well as
abstracts originating from publications that may be protected by U.S.
copyright law.
NLM assumes no responsibility or liability associated with use of
copyrighted material, including transmitting, reproducing,
redistributing, or making commercial use of the data. NLM does not
provide legal advice regarding copyright, fair use, or other aspects of
intellectual property rights. Persons contemplating any type of
transmission or reproduction of copyrighted material such as abstracts
are advised to consult legal counsel.
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