Nl User: Kristina Hettne

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Name: Kristina Hettne

Joined: Monday 03 August 2009 09:00:59 (UTC)

Last seen: Sunday 26 February 2017 22:18:45 (UTC)

Email (public): k.m.hettne [at] lumc.nl

Website: http://www.biosemantics.org/

Location: Leiden, Netherlands

Kristina Hettne has been credited 29 times

Kristina Hettne has an average rating of:

4.5 / 5

(2 ratings in total)

for their items

I am a bioinformatician working in the field of biosemantics


Other contact details:

Not specified

Interests:

Toxicogenomics, Bioinformatics, Text mining

Field/Industry: Academic

Occupation/Role(s): Scientific Researcher

Organisation(s):

Leiden University Medical Center

 

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Pack

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Pack BioSemantics Concept Profile Generation Workflows


Created: 2014-06-04 12:31:09 | Last updated: 2014-06-04 13:01:44

This pack compiles concept profile-generation workflows by the LUMC/EMC Biosemantics groups.This work is made possible by EU projects 'Workflow Forever' (www.wf4ever-project.org) and RD-Connect (www.rd-connect.eu), and contribution from bioinformatics students from the Hogeschool Leiden.

9 items in this pack

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Workflow

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Workflow Annotate gene list with top ranking concepts (4)

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This workflow annotates a comma separated gene list with a predefined concept set as for example Biological processes or Disease/syndrome. To obtain the particular id for each concept set (e.g. "5" for Biological processes), the workflow listPredefinedConceptSets needs to run first. The output provides us with the top (cutoff) concepts that describe our gene list of interest The workflow is using the anni web services .

Created: 2013-12-03 | Last updated: 2015-04-03

Credits: User Eleni

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Pack HD data interpretation


Created: 2013-09-02 13:18:22 | Last updated: 2015-04-03 21:14:41

This workflow pack, was created in order to further analyse and interpret the results from workflow pack 485 (HD chromatin analysis). The workflows in this pack are using the anni web services, implemented by the Biosemantics group. 

6 items in this pack

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Pack HD chromatin analysis


Created: 2013-08-28 12:17:37 | Last updated: 2016-10-28 15:02:27

This pack is comprised by all workflows used for the integration and the analysis of Huntington's Disease (HD) gene expression data and epigenetic datasets in order to establish links between HD and epigenetic regulation in disease.  

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Workflow

Workflow Mining the Kegg pathway database with the ... (2)

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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: 2012-08-29 | Last updated: 2013-05-15

Credits: User Harish Dharuri

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Pack wf4ever Deliverable 6.3 Pack


Created: 2011-12-02 09:31:26 | Last updated: 2011-12-02 10:21:03

This pack contains (references to) the workflows for GWAS analysis by workflows that perform pathway and GO analysis and biosemantics data interpretation (a special form of text mining). This pack aggregates the deliverable materials for month 8 for Work Package 6. The workflows have not been published in the scientific domain yet, so its content cannot yet be made public. They are available upon request, in particular for reviewers. Please contact Kristina Hettne or Marco Roos (see credit...

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Pack A workflow approach to mine pathway databases provid...


Created: 2012-08-12 14:50:03 | Last updated: 2013-09-06 13:27:45

The pack contains workflows used to generate gene and snp sets for metabolites that were measured in the Illig et al publication. The workflows interrogate the Kegg and Biocyc pathway databases to find genes present in pathways and reactions relevant to a given metabolite.

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