Jonas Wagner

About Jonas Wagner:
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LHA ID: 805RQ6G0V7-7

Location:  Germany

ORCID: Not specified

Joined: 9th Dec 2019

Expertise: Not specified

Tools: Not specified

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LHA - Leipzig Health Atlas

The Leipzig Health Atlas (LHA) is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields in which our team has scientific and clinical expertise.

Programme: This Project is not associated with a Programme

Public web page: https://www.health-atlas.de

Start date: 1st Apr 2016

End date: 28th Feb 2021

LIFE - Leipzig Research Center for Civilization Diseases

Goal of the Leipzig Research Center for Civilization Diseases (LIFE) is the investigation of civilization diseases like depression, diabetes, allergies or cardiovascular diseases. For this purpose we collect as much data as possible regarding health and living conditions of the population in Leipzig and provide these data for scientists of the University of Leipzig and other research institutions.

Programme: Epidemiology

Public web page: http://life.uni-leipzig.de/

Start date: 1st Jan 2009

University of Leipzig

Country:  Germany

City: Leipzig

Web page: https://www.uni-leipzig.de/en/

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas.
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles … are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

Authors: A. Uciteli, C. Beger, J. Wagner, A. Kiel, F. A. Meineke, S. Staubert, M. Lobe, R. Hansel, J. Schuster, T. Kirsten, H. Herre

Date Published: 24th May 2021

Publication Type: Journal article

Ontological modelling and FHIR Search based representation of basic eligibility criteria
LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Abstract (Expand)

Planning clinical studies to check medical hypotheses requires the specification of eligibility criteria in order to identify potential study participants. Electronically available patient data allows … to support the recruitment of patients for studies. The Smart Medical Information Technology for Healthcare (SMITH) consortium aims to establish data integration centres to enable the innovative use of available healthcare data for research and treatment optimization. The data from the electronic health record of patients in the participating hospitals is integrated into a Health Data Storage based on the Fast Healthcare Interoperability Resources standard (FHIR), developed by HL7. In SMITH, FHIR Search is used to query the integrated data. An investigation has shown the advantages and disadvantages of using FHIR Search for specifying eligibility criteria. This paper presents an approach for modelling eligibility criteria as well as for generating and executing FHIR Search queries. Our solution is based on the Phenotype Manager, a general ontological phenotyping framework to model and calculate phenotypes using the Core Ontology of Phenotypes.

Authors: A. Uciteli, C. Beger, J. Wagner, T. Kirsten, F. A. Meineke, S. Staubert, M. Lobe, H. Herre

Date Published: 26th Apr 2021

Publication Type: Journal article

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science
LHA - Leipzig Health Atlas, oBIG - omics Bioinformatics for Health

Abstract (Expand)

Background: oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and … visualization. Results: These functionalities are now available as interactive web-browser application for a broader user audience interested in extracting detailed information from high-throughput omics data sets pre-processed by oposSOM. It enables interactive browsing of single-gene and gene set profiles, of molecular 'portrait landscapes', of associated phenotype diversity, and signalling pathway activation patterns. Conclusion: The oposSOM-Browser makes available interactive data browsing for five transcriptome data sets of cancer (melanomas, B-cell lymphomas, gliomas) and of peripheral blood (sepsis and healthy individuals) at www.izbi.uni-leipzig.de/opossom-browser .

Authors: Henry Loeffler-Wirth, Jasmin Reikowski, Siras Hakobyan, Jonas Wagner, Hans Binder

Date Published: 1st Dec 2020

Publication Type: Journal article

Metabolite Investigator v0.1.2 (Docker Image)
Genetical Statistics and Systems Biology

#UPDATE

This archive has been replaced by the GitLab docker registry. Follow the Link under Data Portal (https://gitlab.com/imise-genstat/metabolite-investigator-archive/container_registry/1612096) to find all previous versions of the app (starting from 0.1.6). The images can be downloaded and run using a working docker environment using the following commands:

Using the initial release version 0.1.6 as an example

docker pull registry.gitlab.com/imise-genstat/metabolite-investigator-archive:0.1.6 ...

Creators: Markus Scholz, Jonas Wagner, Carl Beuchel, Holger Kirsten

Submitter: Carl Beuchel

Data file type: Other OMICs Data

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Health Atlas

The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

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