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Showing 14 results. Use the filters on the left and the search box below to refine the results.
Wsdl: http://ws.adaptivedisclosure.org/axis/services/SearcherWS?wsdl or http://xml.nig.ac.jp/wsdl/OMIM.wsdl or http://ws.adaptivedisclosure.org/axis/services/NERecognizerService?wsdl or http://bubbles.biosemantics.org:8080/axis/services/SynsetServer/SynsetServer.jws?wsdl

Workflow BioAID_DiseaseDiscovery_RatHumanMouseUnipr... (4)

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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...

Created: 2008-12-15 | Last updated: 2011-08-11

Credits: User Marco Roos Network-member AID

Workflow BioAID_ProteinDiscovery_filterOnHumanUnipr... (11)

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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...

Created: 2009-05-28

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

Attributions: Workflow BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter

Workflow BioAID_ProteinDiscovery (8)

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The workflow extracts protein names from documents retrieved from MedLine based on a user Query (cf Apache Lucene syntax). The protein names are filtered by checking if there exists a valid UniProt ID for the given protein name.

Created: 2010-05-10 | Last updated: 2013-08-16

Credits: User Marco Roos Network-member AID

Workflow BioAID_ProteinToDiseases (1)

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This workflow was based on BioAID_DiseaseDiscovery, changes: expects only one protein name, adds protein synonyms). This workflow finds diseases relevant to the query string via the following steps: A user query: a single protein name Add synonyms (service courtesy of Martijn Scheumie, Erasmus University Rotterdam) Retrieve documents: finds relevant documents (abstract+title) based on query Discover proteins: extract proteins discovered in the set of relevant abstracts 5. Link proteins ...

Created: 2007-11-14 | Last updated: 2007-11-15

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

Attributions: Workflow BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter

Workflow Discover_proteins_from_text (2)

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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.

Created: 2007-11-15 | Last updated: 2007-11-15

Credits: User Marco Roos Network-member AID

Workflow Retrieve_bio_documents (2)

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This workflow retrieves relevant documents, based on a query optimized by adding a string to the original query that will rank the search output according to the most recent years. The added string adds years with priorities (most recent is highest); it starts at 2007.

Created: 2007-12-10 | Last updated: 2007-12-10

Credits: User Marco Roos User Edgar Network-member AID

Workflow Discover_entities (2)

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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 ...

Created: 2007-12-10 | Last updated: 2007-12-10

Credits: User Marco Roos User Sophia katrenko Network-member AID

Workflow Retrieve_documents_MR1 (1)

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This workflow applies the search web service from the AIDA toolbox. Comments: This search service is based on lucene defaults; it may be necessary to optimize the querystring to adopt the behaviour to what is most relevant in a particular domain (e.g. for medline prioritizing based on publication date is useful). Lucene favours shorter sentences, which may be bad for subsequent information extraction.

Created: 2007-12-10

Credits: User Marco Roos User Edgar Network-member AID

Workflow omim and pathways (2)

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This workflow searches OMIM for entries associated with a particular disease in OMIM, returns the IDs and maps them to Kegg Gene IDs. For each gene, it then gets the description and any corresponding pathways those genes are involved with

Created: 2009-03-03 | Last updated: 2009-11-02

Credits: User Katy Wolstencroft User Paul Fisher

Attributions: Workflow Get Kegg Gene information

Workflow wf4ever_document_extraction_and_storage (1)

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The workflow uses parts of the existing BioAid workflow by Marco Roos (http://www.myexperiment.org/workflows/74.html) The workflow stores found articles in a Solr database. Make sure that Solr is running in the correct directory (stored in the Solr_directory value).

Created: 2013-07-24 | Last updated: 2013-08-29

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