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Scientific workflow and its applications on Docking, virtual screening
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LIP6, University of Paris 6
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Ph.D candidate
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Workflow
Pathways and Gene annotations for QTL region
(7)
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
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Workflow
Pathways and Gene annotations for QTL region
(1)
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: 2010-11-15
| Last updated: 2010-11-16
Credits:
Paul Fisher
Attributions:
Pathways and Gene annotations for QTL region
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Workflow
Pathways and Gene annotations for RefSeq ids
(1)
This workflow searches for genes which were found to be differentially expressed from a microarray study in the mouse, Mus musculus. The workflow requires an input of gene ref_seq identifiers. Data is then extracted from BioMart to annotate each of the genes found for each ref_seq id. The Entrez and UniProt identifiers are then sent to KEGG to obtain KEGG gene identifiers. The KEGG gene identifiers are then used to search for pathways in the KEGG pathway database.
Created: 2010-11-15
| Last updated: 2010-11-15
Credits:
Paul Fisher
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Workflow
BioAID_DiseaseDiscovery_RatHumanMouseUnipr...
(4)
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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