Workflow Entry: Discover_proteins_from_text

Created at: 15/11/07 @ 08:58:00      Last updated: 15/11/07 @ 09:12:34
Information Version 2 (latest) (of 2)
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Version created on: 15/11/07 @ 08:58:00 by: Marco Roos   |   Revision comments Expand

Last edited on: 15/11/07 @ 09:12:34 by: Marco Roos

Title: Discover_proteins_from_text

Type: Taverna 1


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Information Description

This workflow discovers proteins from plain text. It is built around the AIDA 'Named Entity Recognize' web service by Sophia Katrenko (service based on LingPipe), from which output it filters out proteins. The Named Recognizer services uses the pre-learned genomics model, named 'MedLine', to find genomics concepts in plain text.


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Information Workflow Components

Inputs (1)
Processors (3)
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Outputs (1)
Links (4)
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Information Workflow Type

Taverna 1

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Version History

Earliest Version:
[1] - Discover_proteins_from_text

Created on: Thursday 15 November 2007 @ 08:58:00 (GMT)

Created by: Marco Roos

Revision comments:

None

Latest Version:
[2] - Discover_proteins_from_text

Created on: Thursday 15 November 2007 @ 08:58:00 (GMT)

Created by: Marco Roos

Last edited on: Thursday 15 November 2007 @ 09:12:34 (GMT)

Last edited by: Marco Roos

Revision comments:

None



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Workflow Other workflows that use similar services (5)

Only the first 2 workflows that use similar services are shown. View all workflows that use these services.


Original Uploader

Workflow BioAID_ProteinDiscovery_filterOnHumanUniprot_perDoc_html (v11)

Created: 28/05/09 @ 12:21:05

Credits: User Marco Roos User Martijn Schuemie Network-member AID Network-member AID_myGrid_collaboration

Attributions: Workflow BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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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):

Show View Download Download (v11)

Original Uploader

Workflow BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter (v4)

Created: 15/12/08 @ 20:46:09 | Last updated: 11/08/11 @ 09:22:23

Credits: User Marco Roos Network-member AID

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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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: 4034 times | Downloaded: 616 times

Tags (9):

Show View Download Download (v4)

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Non-Information Resource URI: http://www.myexperiment.org/workflows/80


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