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HTT-HPO concept profile match result

Created: 2014-10-20 08:26:32 | Last updated: 2014-10-20 08:35:28

Credits: Marco Roos Rajireturn BioSemantics

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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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

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The Hypothesis for the wf4ever Demo Pack 2013

Created: 2013-01-30 14:06:43 | Last updated: 2013-01-30 14:07:25

Credits: Marco Roos

License: Creative Commons Attribution-Share Alike 3.0 Unported License

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New run.sh for Taverna 2 (in case of problems with n...

Created: 2009-05-28 09:25:03

Credits: Marco Roos

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: Trident (Package)

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From biologist to web service to Taverna to myExperi...

Created: 2008-03-21 19:00:12 | Last updated: 2008-03-23 10:39:27

Credits: Marco Roos Martijn Schuemie AID myGrid

License: Creative Commons Attribution-Share Alike 3.0 Unported License

File type: AVI video

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Get properties of drugs for genes by Entre... (3)

Given a Entrez gene_id the workflow extracts features of its protein (e.g. function, cellular localization and name) and properties of specific drugs for this protein (including activity, PSA, RO5, Smiles and molweight). This workflow uses 3 different services of OpenPHACTS (Target Pharmacology, Compound Information, Target Information).

Created: 2015-07-24 | Last updated: 2015-07-28

Credits: Katerina Nosikova Marco Roos Eleni Eelke van der Horst Elizaveta Besedina

Match concept to HPO profiles (1)

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This workflow matches a query concept to the list of Human Phenotypes. The Human Phenotypes are the subset of the Human Phenotype Ontology for which we have a mapped UMLS concept available and a concept profile. 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/5.pdf Concept Profile Database: July 2012

Created: 2014-10-20

Credits: Marco Roos BioSemantics

Attributions: Match concept profiles Get concept information

HPO-UMLS-ConceptID mapping (1)

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Generate HPO-Concept profiles via HPO-UMLS mappings. The result is a list of Concept IDs corresponding to Concept profiles for UMLS concepts that approximate HPO concepts. The output is a table of UMLS-ID, HPO- ID, COncept-ID rows.

Created: 2014-10-20

Credits: Marco Roos BioSemantics

Get concept suggestions from term (1)

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This workflow suggests concept ids that match the query term. The user can run this workflow with any term of interest as for example "human", "htt", "Transcription" etc, and will get suggestions for concept ids together with descriptions. Then can choose the concept id that matches the best to her/his needs and use it to the rest of the CPA workflows.

Created: 2015-02-18

Credits: Eelke van der Horst Kristina Hettne Marco Roos Eleni

Attributions: Get concept suggestions from term

OPS REST services (1)

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Library of REST services developed for the Open Pharmacological Space (OPS) by the OpenPHACTS project. Usage: 1. Copy-paste a service into your workflow 2. Add an output to responseBody 3. Run the workflow (this will produce output in XML) 4. Copy the XML output 5. Go back to the design window and add the XPath widget to the canvas 6. Link the responseBody output to the XPath widget input 7. Paste the XML output to the example window in the XPath configure window 8. Select the desired eleme...

Created: 2013-07-06

Credits: Marco Roos Open PHACTS

OPS_FreetextToTargetInfo (1)

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Workflow to retrieve target information for the concepts as refered to by humans (the input). Known issues: It produces error values for the concepts returned by ConceptWiki that are apparently not present in OPS (e.g. for "ezh2" and limit=10, it gives 7/10 error values vs "ezh2 (homo sapiens)" giving 2 valid values).

Created: 2013-06-18

Credits: Marco Roos Katy Wolstencroft paul groth

Free text search to Concept Wiki URI (4)

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Free text search of concept wiki using the Openphacts "Map free text to a concept url based on semantic tag" ie /search/byTag. Search for either compounds or targets depending on the input uuid for "searchType" and filter by source authority with the "branch" input

Created: 2013-06-24 | Last updated: 2013-06-24

Credits: Ian Dunlop Katy Wolstencroft Marco Roos paul groth

GWAS to biomedical concept (3)

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Genome-Wide Association studies (GWAS) with metabolomic phenotypes yield several statistically significant SNP-metabolite associations. To understand the biological basis of the association, scientists typically dwell on identifying genes in the vicinity of the SNP and the possible pathways that the gene participates in. The information needed to arrive at an understanding of the mechanistic basis of the association requires integration of disparate data sources. The purpose of this workflow ...

Created: 2013-04-15 | Last updated: 2014-07-14

Credits: Kristina Hettne Harish Dharuri Marco Roos Reinout van Schouwen

Annotate a gene list with disease concepts (1)

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Purpose: Currently, this workflow takes a list of genes and a concept set as input, calculates the matching score between these and finds the concept that contributes the most to the match. Author comments: The workflow is in Beta stage. It runs, but needs more testing with different parameter settings. This workflow can be used together with other workflows in this pack: http://www.myexperiment.org/packs/368 for functional gene annotation and knowledge discovery.

Created: 2013-02-06

Credits: Kristina Hettne Reinout van Schouwen Marco Roos BioSemantics

Attributions: SNPs to Concept Set through Concept Profile Matching v2

Match concept profiles with predefined set (2)

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Purpose of workflow: The workflow can be used to match a set of concept profiles with predefined set of concept profiles. Result: A list of concepts ordered by their match to the query concept profiles.

Created: 2013-02-05 | Last updated: 2014-07-14

Credits: Kristina Hettne Marco Roos Reinout van Schouwen BioSemantics

Find Supporting Documents (6)

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This workflow finds documents that serve as evidence for the association between two concepts. Results: Document titles Document identifiers There seems to be a bug at the moment, since it returns empty values.

Created: 2012-06-26 | Last updated: 2014-07-14

Credits: Kristina Hettne Marco Roos Reinout van Schouwen Martijn Schuemie BioSemantics

SNPs to Concept Set through Concept Profil... (6)

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Purpose: Currently, this workflow takes one SNP and a concept set as input, calculates the matching score between these, finds co-occuring documents between the query concept and the match concept, finds the concept that contributes the most to the match, and the documents that support this finding. Author comments: The workflow is in Beta stage. It runs, but needs more testing with different parameter settings. This workflow can be used together with other workflows in this pack: http://www...

Created: 2012-06-26 | Last updated: 2013-02-05

Credits: Kristina Hettne Eleni Harish Dharuri Reinout van Schouwen Marco Roos Martijn Schuemie BioSemantics

Attributions: Find Supporting Documents SNP_ID2EntrezGene_ID DatabaseID to ConceptID Match gene lists based on information in literature Match concept profiles Explain concept scores

Get Concept IDs (5)

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Purpose: The workflow retrieves the concepts within a concept set. The Web service/workflow currently returns no values (bug).

Created: 2012-07-06 | Last updated: 2014-07-14

Credits: Kristina Hettne Reinout van Schouwen Martijn Schuemie Marco Roos BioSemantics

Find co-occurring documents (6)

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Purpose: This workflow search an indexed literature database for documents mentioning both of the input concepts. Author comments: Currently, PubMed is the underlying data source.

Created: 2012-07-13 | Last updated: 2014-07-14

Credits: Kristina Hettne Reinout van Schouwen Marco Roos Martijn Schuemie BioSemantics

Mining the Kegg pathway database with the ... (1)

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Genome-Wide Association studies (GWAS) with metabolomic phenotypes yield several statistically significant SNP-metabolite associations. To understand the biological basis of the association, scientists typically dwell on identifying genes in the vicinity of the SNP and the possible pathways that the gene participates in. The information needed to arrive at an understanding of the mechanistic basis of the association requires integration of disparate data sources. The purpose of this workflow ...

Created: 2013-01-30

Credits: Marco Roos

List Concept Sets (3)

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Pupose: The workflow returns a list of all Concept Set IDs currently available in the database. The Concept Sets have an hierarchical structure that can be inferred by referring to the parent Concept Set ID.

Created: 2012-07-06 | Last updated: 2014-07-14

Credits: Kristina Hettne Marco Roos Reinout van Schouwen Martijn Schuemie BioSemantics

Match concept profiles (6)

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Purpose of workflow: The workflow can be used to match a set of concept profiles with another set of concept profiles. Result: A list of concepts ordered by their match to the query concept profiles.

Created: 2011-12-02 | Last updated: 2014-07-14

Credits: Marco Roos Kristina Hettne Martijn Schuemie Reinout van Schouwen

Get concept information (5)

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The workflow takes a (list of) concept ID(s) as input and returns the profile, ID, definition and name of the concept.

Created: 2012-07-06 | Last updated: 2014-07-14

Credits: Kristina Hettne Reinout van Schouwen Marco Roos Martijn Schuemie BioSemantics

DatabaseID to ConceptID (7)

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Purpose: This workflow maps input Identifiers, common database identifiers, to the Concept Identifiers from the EMC ontology. Result: Concept Identifiers from the EMC ontology. Comments: Database: one of CAS, DRUG, etc. The supported databases are listed below (database, description, example). CAS, Chemical Abstracts Service registry number, 64-17-5. DRUG, Drug Bank, DB00316. AF, Affymetrix, 200007_at. CHEB, ChEBI, 16236. CHID, ChemIDplus, 0000050000. EG, Entrez-Gene, 3064. GO, Gene Ontol...

Created: 2012-06-25 | Last updated: 2014-07-14

Credits: Marco Roos Martijn Schuemie Reinout van Schouwen BioSemantics

Match gene lists based on information in l... (7)

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[THIS WORKFLOW IS IN BETA STAGE] This workflow computes the match between two lists of Entrez Gene Identifiers by means of concept profile matching (Jelier et al., van Haagen et al.). The result of this is a list of concepts ordered by their matching score (the length of the list set by maxMatchNr). Of this list the summed scores are explained by computing the concepts that contribute most to the combination of the matching genes. Example to explain (by analogy): When a group of informatic...

Created: 2012-04-17 | Last updated: 2012-04-25

Credits: Marco Roos Reinout van Schouwen Eleni Kristina Hettne BioSemantics

Attributions: Match concept profiles Explain concept scores

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

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

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

Analysing workflows (3)

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This workflows analyses workflows stored at the myExperiment site. It is used in the paper submitted to the Workshop on Scientific Workflow 2009. The workflow shows the task usage in the Taverna workflows stored at the myExperiment site The amount of services used The amount of local processors used The amount of scripting tasks The amount of sub workflows Furthermore it classifies the local services based on their intended function. The workflow has two inputs: ...

Created: 2009-05-06 | Last updated: 2009-05-06

Credits: Wassinki Pieter Neerincx Katy Wolstencroft 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

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

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

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

Link_protein_to_OMIM_disease (1)

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Created: 2007-12-10

Credits: Marco Roos AID

Flatten_and_make_unique (1)

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Created: 2007-12-10

Credits: Marco Roos AID

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

TestIteratorStrategy_withCloning (2)

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This workflow implements a strategy for this problem: > I would like to perform an iteration including a dot product between > a list and a list of lists; example: > Input: > > [1] (1) > [A,B,C] (2) > [[a,b],[c,d],[e,f]] (3) > > Desired output: > > [1Aa, 1Ab, 1Bc, 1Bd, 1Ce, 1Cf] In this implementation a java beanshell is used to clone the items in list 2 as many times per item as there are items in the sublists of list 3. The iteration stra...

Created: 2007-11-29 | Last updated: 2007-11-29

Credits: Marco Roos

CloneItemsInList (1)

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Utility workflow that clones an item copy_number times. You can use this to work around standard iteration strategies, e.g. in combination with the CountListItems workflow. Workflow examples: TestIterationStrategy_withClones. For an alternative approach see TestIterationStrategy_withNesting. Example I/O: input: A copy_number: 3 result: [A,A,A] input: [A,B,C] copy_number: 3 result: [[A,A,A][B,B,B][C,C,C]] input: [A,B,C] copy_number: [3,2] result: [[[A,A,A],[A,A]][[B,B,B],[B,B]],[[C,C,C],...

Created: 2007-11-29

Credits: Marco Roos

TestIteratorStrategy_withNesting (1)

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Implementation of the iteration workaround by Tom Oin conform the Q&A below. The nested workflow 'NestedProcessor' is called that to conform to Tom's explanation. For an alternative solution using a java beanshell to clone list items see 'TestIteratorStrategy_withCloning. This workflow implements the following Q&A: Marco Roos wrote: > Dear Taverna user, > > Issue 1: Complex iteration > > I would like to perform an iteration including a dot product between > a list and a list of li...

Created: 2007-11-29

Credits: Marco Roos Tomoinn

TestIterator (1)

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Workflow to experiment with list iteration strategies. Look at metadata of nested workflow 'Concatenate' to see the current iteration strategy.

Created: 2007-11-28

Credits: 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

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

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

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

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

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