Workflows

Pathways and Gene annotations for QTL region (7)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in the mouse, Mus musculus. The workflow requires an input of: a chromosome name or number; a QTL start base pair position; QTL end base pair position. Data is then extracted from BioMart to annotate each of the genes found in this region. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to searcg for pathways in the KEGG path...

Created: 2009-11-19 | Last updated: 2012-09-07

Credits: Paul Fisher

Entrez Gene to KEGG Pathway (5)

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This workflow takes in Entrez gene ids then adds the string "ncbi-geneid:" to the start of each gene id. These gene ids are then cross-referenced to KEGG gene ids. Each KEGG gene id is then sent to the KEGG pathway database and its relevant pathways returned.

Created: 2009-12-04 | Last updated: 2010-11-30

Credits: Paul Fisher

Microarray CEL file to candidate pathways (2)

This workflow takes in a CEL file and a normalisation method then returns a series of images/graphs which represent the same output obtained using the MADAT software package (MicroArray Data Analysis Tool) http://www.bioinf.manchester.ac.uk/MADAT/index.html. Also retruned by this workflow are a list of the top differentialy expressed genes (size dependant on the number specified as input - geneNumber), which are then used to find the candidate pathways which may be influencing the observed ch...

Created: 2008-02-08 | Last updated: 2009-02-13

Credits: Paul Fisher Saeedeh

Pathways and Gene annotations for Arabidop... (2)

This workflow searches for genes obtained from affy_ath1 affymetrix probeset identifiers. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to searcg for pathways in the KEGG pathway database.

Created: 2009-03-06 | Last updated: 2009-12-03

Credits: Paul Fisher Peter Li

Attributions: Pathways and Gene annotations for QTL region

Pathways and Gene annotations for QTL region (2)

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This workflow searches for genes which reside in a QTL (Quantitative Trait Loci) region in the Pig, Sus scrofa. The workflow requires an input of: a chromosome name or number; a QTL start base pair position; QTL end base pair position. Data is then extracted from BioMart to annotate each of the genes found in this region. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to searcg for pathways in the KEGG pathway ...

Created: 2009-11-20 | Last updated: 2009-11-20

Credits: Paul Fisher

Attributions: Pathways and Gene annotations for QTL region

Query dbsnp, transform to HTML (1)

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Created: 2009-05-21 | Last updated: 2009-05-21

Credits: Pierre Lindenbaum

Basic eSearch/eFetch cycle (1)

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This is a basic eSearch/eFetch workflow created with taverna and using eUtils from NCBI. It accepts a query term as input (at the moment, for testing purposes, this is a fixed string), interrogate eSearch to retrieve the list of related sequences on the Nucleotide database, and use eFetch to retrieve the corresponding sequences. I wrote this workflow one year ago, when I was trying to understand how taverna and eUtils work; I suspect it broken, and of course it could be enhanced, so I am ...

Created: 2008-12-04 | Last updated: 2008-12-04

Credits: Giovanni Dall'Olio

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

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

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