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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: Marco Roos Martijn Schuemie AID AID_myGrid_collaboration

Attributions: BioAID_DiseaseDiscovery_RatHumanMouseUniprotFilter

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: Marco Roos Edgar AID

Demo of statistics webservice invoked from... (1)

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Created: 2009-03-29

Credits: David De Roure

Extract_proteins (2)

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This workflow filters protein_molecule-labeled terms from an input string(list). The result is a tagged list of proteins (disregarding false positives in the input). Internal information: This workflow is a copy of 'filter_protein_molecule_MR3' used for the NBIC poster (now in Archive).

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

Credits: Marco Roos

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: Marco Roos Sophia katrenko AID

Demo_DiseaseDiscovery_byHumanUniprot_scaffold (1)

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This workflow finds disease relevant to the query string via the following steps: 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. Retrieve documents: finds 'maximumNumberOfHits' relevant documents (abstract+title) based on query (the AIDA service inside is based on Apache's Lucene)...

Created: 2007-12-10

Credits: Marco Roos AID

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

Lucene_bioquery_optimizer_MR1 (1)

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This workflow does four things: it retrieves documents relevant for the query string it discovers entities in those documents, these are considered relevant entities it filters proteins from those entities (on the tag protein_molecule) 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, ...

Created: 2007-12-10

Credits: Marco Roos AID

Demo of ChemSpider InChi to SMILES webserv... (1)

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Created: 2009-03-28 | Last updated: 2009-03-28

Credits: David De Roure

Explain concept scores (7)

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Purpose of workflow: This workflow takes two concept ids as input and returns the top ranking "B" concepts according to Swanson's ABC model of discovery, where the relationships AB and BC are known and reported in the literature, and the implicit relationship AC is a putative new discovery. It might also be the case that AC is already known. In that case AC does not represent a new discovery but will still be returned (see workflow example values). The B concepts are returned sorted on the pe...

Created: 2012-02-07 | Last updated: 2014-07-14

Credits: Reinout van Schouwen