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Items tagged with "text_mining" (21)

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Marco Roos

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Concept Profile of phenotype Chorea

Created: 2014-10-20 08:34:10

Credits: Marco Roos BioSemantics

License: Creative Commons Attribution-Share Alike 3.0 Unported License

Concept Profile generated from HPO term 'Chorea' via mapping to the corresponding UMLS phenotype concept.The profile contains ranked associations with Chorea conform mutual information content derived from co-occurrence in MedLine abstracts.Versions:HPO-UMLS mapping: Winnenburg, R., & Bodenreider, O. (2014). Coverage of Phenotypes in Standard Terminologies. In Proceedings of the ISMB’2014 SIG meeting “BioLINK.” Retrieved from http://phenoday2014.bio-lark.org/pdf/...

File type: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet

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Taverna 1

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Marco Roos

DiscoverProteinLink (2)

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COMPETITION: For friends only: If you find any two topics that return true positives with this workflow I will buy you a bottle of wine (or equivalent). Terms: if we confirm that the protein was indeed never mentioned together with both input topics in one article, we will publish this together. ---- This workflow implements Swanson's prinicple with services from the AIDA toolbox. It tries to find proteins that link two topics, while they never mentioned together with both topics in ...

Created: 2007-10-03 | Last updated: 2007-11-15

Credits: Marco Roos AID

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Marco Roos

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: Marco Roos AID

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Marco Roos

ProteinSynonymsToQuery (2)

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This workflow uses Martijn Schuemie's protein synonym service to produce synonyms and a new query string from the input query term. The service is limited to proteins, enzymes and genes. An input query that is a boolean string will be split and processed, but the boolean logic of the input query will be lost. Workflow URL: http://rdf.adaptivedisclosure.org/~marco/BioAID/Public/Workflows/BioAID/ProteinSynonymsToQuery.xml

Created: 2007-10-03 | Last updated: 2007-11-13

Credits: Marco Roos Martijn Schuemie AID

Taverna 2

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Marco Roos

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: Marco Roos AID

Taverna 1

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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

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Marco Roos

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: Marco Roos AID

Taverna 1

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Marco Roos

BioAID_Discover_proteins_from_text_plus_sy... (1)

This workflow discovers proteins from plain text and adds synonyms using Martijn Schuemie's proteins synonym service. Proteins are discovered with 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

Credits: Marco Roos Martijn Schuemie AID

Taverna 1

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Marco Roos

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

Taverna 1

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Hamish McWilliam

EBI_Whatizit (1)

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Perform a text-mining analysis of an input text document using the EBI's Whatizit tool (http://www.ebi.ac.uk/webservices/whatizit/info.jsf). Whatizit provides a number of text-mining pipelines which can can detect various terms of biological interest in text documents. For example finding gene names and mapping them to UniProtKB identifiers, finding chemical terms and mapping them to ChEBI, etc.

Created: 2008-07-09

Credits: Hamish McWilliam

Taverna 1

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Marco Roos

BioAID_EnirchBioModelWithProteinsFromText (7)

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This workflow is for demonstration purposes only. Please contact the authors if you wish to try it. We will gladly collaborate with you. Summary This workflow extracts proteins and protein relations from Medline. Extracted protein names (symbols of at least 3 characters) are validated against mouse, rat, and human UniProt symbols, so the results are limited to these species. This workflow follows the following basic steps: it retrieves documents relevant for the query string i...

Created: 2009-05-16 | Last updated: 2009-05-16

Credits: Marco Roos Sophia katrenko Andrew Gibson M. Scott Marshall Willem van Hage Edgar Martijn Schuemie AID

Taverna 2

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Francois Belleau

Text search within sparql point (1)

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This workflow make possible full text search within different sparql point made available by the Bio2RDF project.

Created: 2009-01-19

Credits: Francois Belleau

Taverna 2

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Francois Belleau

Author's collaborators according to pubmed (1)

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SELECT distinct ?s2 FROM <http://atlas.bio2rdf.org/sparql> WHERE { ?s1 ?p1 ?o1 . ?o1 bif:contains "author" . ?s2 ?p2 ?s1 . FILTER( regex(?s1, "pubmed") ) } followed by SELECT ?creator, count() FROM <http://localhost:8890/sparql> WHERE { ?s1 ?p1 . ?s1 ?p2 ?o2 . FILTER( regex(?o2, "author")) ?s1 ?creator . } ORDER BY DESC(count())

Created: 2009-01-20 | Last updated: 2009-01-20

Credits: Francois Belleau

Taverna 2

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Francois Belleau

What is Paget's disease sparql query example (3)

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SELECT distinct ?s1 FROM <http://atlas.bio2rdf.org/sparql> WHERE { ?s1 ?p1 ?o1 . ?o1 bif:contains "paget" . FILTER( regex(?s1, "omim") OR regex(?s1, "geneid") OR regex(?s1, "uniprot")) } followed by SELECT ?type1, count(*) FROM <http://localhost:8890/sparql> WHERE { ?s1 ?p1 ?o1 . ?o1 bif:contains "paget" . ?s1

Created: 2009-01-20

Credits: Francois Belleau

Taverna 2

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Marco Roos

Gene expression interpretation by the Glob... (1)

This workflow adds meaning to gene expresion values by performing a standard and a literature weighted Global Test. Gene expression is expected to be from Affymetrix microarrays, for which an RMA normalization and entrez Gene ID mapping/summation is performed. Original workflow is by Dennis Leenheer, edits by Marco Roos. Scripts by Kristina Hettne, acknowledging Rob Jellier, Jelle Goeman, and Peter-Bram 't Hoen. The workflow was created for the LUMC BioSemantics group, part of the Human Gen...

Created: 2011-04-26 | Last updated: 2011-04-26

Credits: Marco Roos

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