Version 2 (latest)
(of 2)
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Version created on:
10/12/07 @ 21:48:33
by:
Marco Roos
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Revision comments
Last edited on: 10/12/07 @ 22:54:42 by: Marco Roos
Title: Discover_entities
Type: Taverna 1
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Description
This workflow contains the 'Named Entity Recognize' web service from the AIDA toolbox, created by Sophia Katrenko. It can be used to discover entities of a certain type (determined by 'learned_model') in documents provided in a lucene output format.
Known issues:
The output of NErecognize contains concepts with / characters, breaking the xml. For post-processing its results it is better to use string manipulation than xml manipulations. The output is per document, which means entities will be redundant if they occur in more than one document.
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Option 1:
Note: you need to have both the WHIP Launcher and the Taverna myExperiment/WHIP plugin installed on your machine for this to work. See here for information.
Option 2:
Copy and paste this link into File > 'Open workflow location...'
http://www.myexperiment.org/workflows/111/download?version=2
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Earliest Version:
[1] - Discover_entities
Latest Version:
[2] - Discover_entities
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(5)
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Original Uploader |
Created: 28/05/09 @ 12:21:05
Credits:
Attributions:
License: Creative Commons Attribution-Share Alike 3.0 Unported License
This workflow finds proteins relevant to the query string via the following steps:
A user query: a single gene/protein name. E.g.: (EZH2 OR "Enhancer of Zeste").
Retrieve documents: finds 'maximumNumberOfHits' relevant documents (abstract+title) based on query (the AIDA service inside is based on Apache's Lucene)
Discover proteins: extract proteins discovered in the set of relevant abstracts with a 'named entity recognizer' trained on genomic terms using a Bayesian approach; the AIDA serv...
Rating: 0.0 / 5 (0 ratings) | Versions: 11 | Reviews: 0 | Comments: 1 | Citations: 0 Viewed: 454 times | Downloaded: 167 times Tags (9): |
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Download (v11)
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|
Original Uploader |
Created: 15/12/08 @ 20:46:09 | Last updated: 11/08/11 @ 09:22:23
Credits:
License: Creative Commons Attribution-Share Alike 3.0 Unported License
This workflow finds disease relevant to the query string via the following steps: 1. A user query: a list of terms or boolean query - look at the Apache Lucene project for all details. E.g.: (EZH2 OR "Enhancer of Zeste" +(mutation chromatin) -clinical); consider adding 'ProteinSynonymsToQuery' in front of the input if your query is a protein. 2. Retrieve documents: finds 'maximumNumberOfHits' relevant documents (abstract+title) based on query (the AIDA service inside is based on Apa...
Rating: 4.0 / 5 (2 ratings) | Versions: 4 | Reviews: 0 | Comments: 3 | Citations: 0 Viewed: 4032 times | Downloaded: 616 times Tags (9): |
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Download (v4)
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Linked Data
Non-Information Resource URI: http://www.myexperiment.org/workflows/111
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