Retrieve_bio_documents

Created: 2007-12-10 22:15:54 Last updated: 2007-12-10 22:45:49

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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.

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Workflow Components

Inputs (4)

Name	Description
query_string
document_index
search_field
maxHits

Processors (2)

Name	Type	Description
Biooptimize_query	workflow	This workflow does four things: 1. it retrieves documents relevant for the query string 2. it discovers entities in those documents, these are considered relevant entities 3. it filters proteins from those entities (on the tag protein_molecule) 4. it removes all terms from the list produced by 3 (query terms temporarily considered proteins) ToDo * Replace step 4 by the following procedure: 1. remove the query terms from the output of NER (probably by a regexp matching on what is inside the tag, possibly case-insensitive) 2. remove tag_as_protein_molecule (obsolete) * Add synonym service/workflow Note that Remove_inputquery has an alternative iteration strategy (dot product instead of cross product). Idem for 'Join' in 'SplitQuery'.
Retrieve	workflow	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.

Beanshells (1)

Name	Description	Inputs	Outputs
Prioritise_lucene_query		query_string priority_string	lucene_query

Outputs (1)

Name	Description
relevant_documents

Links (6)

Source	Sink
query_string	Biooptimize_query:query_string
Biooptimize_query:optimized_lucene_query	Retrieve:queryString
document_index	Retrieve:document_index
maxHits	Retrieve:maxHits
search_field	Retrieve:search_field
Retrieve:relevant_documents	relevant_documents

Coordinations (0)

Information Workflow Type

Taverna 1

Information Uploader

Marco Roos

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Information Version 1 (earliest) (of 2)

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Information Favourited By (1)

Hyde Zhang

Information Statistics

3242 viewings

2673 downloads

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Version History

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Retrieve_bio_documents

Created by Marco Roos on Monday 10 December 2007 22:15:54 (UTC)
Retrieve_bio_documents

Created by Marco Roos on Monday 10 December 2007 22:15:54 (UTC)

Last edited by Marco Roos on Monday 10 December 2007 22:45:49 (UTC)

Revision comment:

Added examples for the inputs

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Comments (2)

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Paul Fisher

Hi Marco,

Could you please add some instructions on what to enter, and maybe some examples.

cheers,

Paul.

Marco Roos	Monday 14 January 2008 12:01:08 (UTC)
	Response to Paul's comment about the instructions. One example for each input is given when you click 'New input' in the run window in Taverna. This is quite minimal; I intend to add more info later and upload a new version.

Other workflows that use similar services (6)

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

Taverna 1

Uploader

Marco Roos

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: Marco Roos Martijn Schuemie AID

Attributions: BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter

Taverna 1

Uploader

Marco Roos

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: Marco Roos Edgar AID