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

LHA ID: 7VV367KHEC-9

Funding codes:

031L0026

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

Human Diseases: No Human Disease specified

Leipzig Health Atlas PALs: Markus Löffler

Project Coordinators: Toralf Kirsten, Judith Schuster

Project start date: 1st Apr 2016

Project end date: 28th Feb 2021

Project Hierarchy

Country: Germany

City: Mittweida

Web page: https://www.cb.hs-mittweida.de/en.html

Institute for Medical Informatics, Statistics and Epidemiology (IMISE)

Country: Germany

City: Leipzig

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

Interdisciplinary Center for Bioinformatics (IZBI)

Country: Germany

City: Leipzig

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

University of Leipzig

Country: Germany

City: Leipzig

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

Ontology-based Phenotyping

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

No description specified

Submitter: Alexandr Uciteli

Studies: Ontological Modelling of Basic Eligibility Criteria, Ontological Modelling of Type 2 Diabetes Mellitus (T2DM) Phenotype, PhenoMan Evaluation with Synthetic FHIR Data

Resources: Basic Eligibility Criteria of an Example Blood Pressure Study, Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan), PhenoMan Evaluation - Synthetic FHIR Data

Snapshots: No snapshots

Created: 9th Mar 2020 at 12:34, Last updated: 29th Jun 2020 at 14:50

PhenoMan Evaluation with Synthetic FHIR Data

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

We evaluated if the PhenoMan returns correct/complete result sets and if it is working with real data. To simulate a FHIR health data store with real data we used Synthea(TM) to generate a large data set and imported it into a HAPI FHIR JPA Server. Based on the synthetic data set we developed ten example queries with different structure and complexity with PhenoMan and SQL. We compared the results of the queries in means of execution time and equality of results.

The detailed steps of the evaluation ...

Submitter: Christoph Beger

Investigation: Ontology-based Phenotyping

Resources: PhenoMan Evaluation - Synthetic FHIR Data

Study type: Not specified

Snapshots: No snapshots

Created: 29th Jun 2020 at 14:53, Last updated: 29th Jun 2020 at 15:31

Ontological Modelling of Basic Eligibility Criteria

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

No description specified

Submitter: Alexandr Uciteli

Investigation: Ontology-based Phenotyping

Resources: Basic Eligibility Criteria of an Example Blood Pressure Study

Study type: Not specified

Snapshots: No snapshots

Created: 30th Apr 2020 at 12:02, Last updated: 30th Apr 2020 at 12:02

Ontological Modelling of Type 2 Diabetes Mellitus (T2DM) Phenotype

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

No description specified

Submitter: Alexandr Uciteli

Investigation: Ontology-based Phenotyping

Resources: Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)

Study type: Not specified

Snapshots: No snapshots

Created: 9th Mar 2020 at 15:12, Last updated: 9th Mar 2020 at 15:14

PhenoMan Evaluation - Synthetic FHIR Data

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

This assay bundles all synthetic FHIR data of the PhenoMan evaluation. The data arised from a subset of a Synthea(TM) generated data set. We truncated some resource types like Encounter and Provider to reduce the size of the data set and to speed up the import in a FHIR health data store.

Submitter: Christoph Beger

Resource type: Result Dataset of Clinical Study

Technology type: Technology Type

Investigation: Ontology-based Phenotyping

Study: PhenoMan Evaluation with Synthetic FHIR Data

Human Diseases: asthma, bronchial disease, hypertension, obesity

SOPs: No SOPs

Data files: PhenoMan Evaluation - AllergyIntolerance FHIR R..., PhenoMan Evaluation - Condition FHIR Resources, PhenoMan Evaluation - Observation FHIR Resources, PhenoMan Evaluation - Patient FHIR Resources

Snapshots: No snapshots

Created: 29th Jun 2020 at 14:58, Last updated: 30th Jun 2020 at 15:49

Basic Eligibility Criteria of an Example Blood Pressure Study

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

No description specified

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Investigation: Ontology-based Phenotyping

Study: Ontological Modelling of Basic Eligibility Crit...

Human Diseases: No human diseases

Models: No Models

SOPs: No SOPs

Data files: Eligibility Criteria Ontology for an Example Bl...

Snapshots: No snapshots

Created: 30th Apr 2020 at 12:06, Last updated: 30th Apr 2020 at 12:30

Ontological Modelling of T2DM Phenotype using Phenotype Manager (PhenoMan)

SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, Onto-Med Research Group

We modelled the algorithm for determining Type 2 Diabetes Mellitus (T2DM) cases presented by PheKB.org using Phenotype Manager (PhenoMan).

Submitter: Alexandr Uciteli

Biological problem addressed: Model Analysis Type

Investigation: Ontology-based Phenotyping

Study: Ontological Modelling of Type 2 Diabetes Mellit...

Human Diseases: diabetes mellitus

Models: No Models

SOPs: No SOPs

Data files: T2DM Case 1 Reasoner Report, T2DM Case 2 Reasoner Report, T2DM Case 3 Reasoner Report, T2DM Case 4 Reasoner Report, T2DM Case 5 Reasoner Report, T2DM Graphical Representation, T2DM Ontology, T2DM Tabular Representation

Snapshots: No snapshots

Created: 9th Mar 2020 at 15:18, Last updated: 10th Mar 2020 at 12:00

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

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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 …

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

PubMed ID: 34042877

Citation: Stud Health Technol Inform. 2021 May 24;278:66-74. doi: 10.3233/SHTI210052.

Created: 2nd Jun 2021 at 10:06, Last updated: 7th Dec 2021 at 17:58

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

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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 …

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

DOI: 10.3205/mibe000219

Citation: Uciteli A, Beger C, Wagner J, Kirsten T, Meineke FA, Staubert S, Lobe M, Herre H: Ontological modelling and FHIR Search based representation of basic eligibility criteria. GMS Med Inform Biom Epidemiol 2021;17(2):Doc05.

Created: 2nd Jun 2021 at 10:15, Last updated: 7th Dec 2021 at 17:58

Deciphering the Transcriptomic Heterogeneity of Duodenal Coeliac Disease Biopsies.

LHA - Leipzig Health Atlas

Abstract (Expand)

Coeliac disease (CD) is a clinically heterogeneous autoimmune disease with variable presentation and progression triggered by gluten intake. Molecular or genetic factors contribute to disease heterogeneity, …

Authors: J. Wolf, E. Willscher, H. Loeffler-Wirth, M. Schmidt, G. Flemming, M. Zurek, H. H. Uhlig, N. Handel, H. Binder

Date Published: 4th Mar 2021

Publication Type: Journal article

PubMed ID: 33806322

Citation: Int J Mol Sci. 2021 Mar 4;22(5). pii: ijms22052551. doi: 10.3390/ijms22052551.

Created: 23rd Apr 2021 at 12:08, Last updated: 7th Dec 2021 at 17:58

Ontological representation, classification and data-driven computing of phenotypes.

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

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Abstract (Expand)

BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and … epidemiological studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term 'phenotype' has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimisation. In the context of a methodological use case 'phenotype pipeline' (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. RESULTS: In this article, we present a Core Ontology of Phenotypes (COP) and the software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model, classify and compute phenotypes from already available data. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated with selected phenotypes including SOFA score, socio-economic status, body surface area and WHO BMI classification based on available medical data. CONCLUSIONS: We developed a novel ontology-based method to model phenotypes of living beings with the aim of automated phenotype reasoning based on available data. This new approach can be used in clinical context, e.g., for supporting the diagnostic process, evaluating risk factors, and recruiting appropriate participants for clinical and epidemiological studies.

Authors: A. Uciteli, C. Beger, T. Kirsten, F. A. Meineke, H. Herre

Date Published: 21st Dec 2020

Publication Type: Journal article

PubMed ID: 33349245

Citation: J Biomed Semantics. 2020 Dec 21;11(1):15. doi: 10.1186/s13326-020-00230-0.

Created: 2nd Jun 2021 at 10:02, Last updated: 7th Dec 2021 at 17:58

oposSOM-Browser: an interactive tool to explore omics data landscapes in health science

LHA - Leipzig Health Atlas, oBIG - omics Bioinformatics for Health

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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 …

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

Date Published: 1st Dec 2020

Publication Type: Journal article

DOI: 10.1186/s12859-020-03806-w

Citation: BMC Bioinformatics 21(1),465

Created: 3rd Feb 2021 at 16:51, Last updated: 7th Dec 2021 at 17:58

Ontological Modelling and Reasoning of Phenotypes

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

(Show All)

Abstract (Expand)

The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological …

Authors: Alexandr Uciteli, Christoph Beger, Toralf Kirsten, Frank A. Meineke, Heinrich Herre

Date Published: 20th Dec 2019

Publication Type: InProceedings

Citation: CEUR Workshop Proceedings. 2019 Sep;2570. issn: 1613-0073.

Created: 9th Mar 2020 at 11:49, Last updated: 7th Dec 2021 at 17:58

Der Leipzig Health Atlas

LHA - Leipzig Health Atlas

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Abstract (Expand)

Die Notwendigkeit des Managements von Forschungsdaten ist von der Forschungscommunity erkannt – Sponsoren, Gesetzgeber, Verlage erwarten und fördern die Einhaltung der guten wissenschaftlichen Praxis, … was nicht nur die Archivierung umfasst, sondern auch die Verfügbarkeit von Forschungsdaten- und ergebnissen im Sinne der FAIR-Prinzipien. Der Leipzig Health Atlas (LHA) ist ein Projekt zur Präsentation und zum Austausch eines breiten Spektrums von Publikationen, (bio) medizinischen Daten (z.B. klinisch, epidemiologisch, molekular), Modellen und Tools z.B. zur Risikoberechnung in der Gesundheitsforschung. Die Verbundpartner decken hierbei einen breiten Bereich wissenschaftlicher Disziplinen ab, beginnend von medizinischer Systembiologie über klinische und epidemiologische Forschung bis zu ontologischer und dynamischer Modellierung. Derzeit sind 18 Forschungskonsortien beteiligt (u.a. zu den Domänen Lymphome, Gliome, Sepsis, Erblicher Darm- und Brustkrebs), die Daten aus klinischen Studien, Patientenkohorten, epidemiologischen Kohorten, teilweise mit umfangreichen molekularen und genetischen Profilen, sammeln. Die Modellierung umfasst algorithmische Phänotypklassifizierung, Risikovorhersage und Krankheitsdynamik. Wir konnten in einer ersten Entwicklungsphase zeigen, dass unsere webbasierte Plattform geeignet ist, um (1) Methoden zur Verfügung zu stellen, um individuelle Patientendaten aus Publikationen für eine Weiternutzung zugänglich zu machen, (2) algorithmische Werkzeuge zur Phänotypisierung und Risikoprofilerstellung zu präsentieren, (3) Werkzeuge zur Durchführung dynamischer Krankheits- und Therapiemodelle interaktiv verfügbar zu machen und (4) strukturierte Metadaten zu quantitativen und qualitativen Merkmalen bereit zu stellen. Die semantische Datenintegration liefert hierzu die Technologien (Ontologien und Datamining Werkzeuge) für die (semantische) Datenintegration und Wissensanreicherung. Darüber hinaus stellt sie Werkzeuge zur Verknüpfung eigener Daten, Analyseergebnisse, öffentlich zugänglicher Daten- und Metadaten-Repositorien sowie zur Verdichtung komplexer Daten zur Verfügung. Eine Arbeitsgruppe zur Applikationsentwicklung und –validierung entwickelt innovative paradigmatische Anwendungen für (1) die klinische Entscheidungsfindung für Krebsstudien, die genetische Beratung, für Risikovorhersagemodelle sowie Gewebe- und Krankheitsmodelle und (2) Anwendungen (sog. Apps), die sich auf die Charakterisierung neuer Phänotypen (z.B. ‚omics‘-Merkmale, Körpertypen, Referenzwerte) aus epidemiologischen Studien konzentrieren. Diese Anwendungen werden gemeinsam mit klinischen Experten, Genetikern, Systembiologen, Biometrikern und Bioinformatikern spezifiziert. Der LHA stellt Integrationstechnologie bereit und implementiert die Anwendungen für die User Communities unter Verwendung verschiedener Präsentationswerkzeuge bzw. Technologien (z.B. R-Shiny, i2b2, Kubernetes, SEEK). Dazu ist es erforderlich, die Daten und Metadaten vor dem Hochladen zu kuratieren, Erlaubnisse der Datenbesitzer einzuholen, die erforderlichen Datenschutzkriterien zu berücksichtigen und semantische Annotationen zu überprüfen. Zudem werden die zugelieferten Modellalgorithmen in einer qualitätsgesicherten Weise aufbereitet und, soweit anwendbar, online interaktiv zur Verfügung gestellt. Der LHA richtet sich insbesondere an die Zielgruppen Kliniker, Epidemiologen, Molekulargenetiker, Humangenetiker, Pathologen, Biostatistiker und Modellierer ist aber unter www.healthatlas.de öffentlich zugänglich – aus rechtlichen Gründen erfordert der Zugriff auf bestimmte Applikationen und Datensätze zusätzliche Autorisierung. Das Projekt wird über das BMBF Programm i:DSem (Integrative Datensemantik für die Systemmedizin, Förderkennzeichen 031L0026) gefördert.

Authors: F. A. Meineke, Sebastian Stäubert, Matthias Löbe, C. Beger, René Hänsel, A. Uciteli, H. Binder, T. Kirsten, M. Scholz, H. Herre, C. Engel, Markus Löffler

Date Published: 19th Sep 2019

Publication Type: Misc

Citation:

Created: 17th Sep 2019 at 08:31, Last updated: 7th Dec 2021 at 17:58

Teratogenic Rubella Virus Alters the Endodermal Differentiation Capacity of Human Induced Pluripotent Stem Cells.

LHA - Leipzig Health Atlas

Abstract (Expand)

The study of congenital virus infections in humans requires suitable ex vivo platforms for the species-specific events during embryonal development. A prominent example for these infections is rubella …

Authors: N. C. Bilz, E. Willscher, H. Binder, J. Bohnke, M. L. Stanifer, D. Hubner, S. Boulant, U. G. Liebert, C. Claus

Date Published: 10th Aug 2019

Publication Type: Not specified

PubMed ID: 31405163

Citation: Cells. 2019 Aug 10;8(8). pii: cells8080870. doi: 10.3390/cells8080870.

Created: 22nd Apr 2020 at 13:03, Last updated: 7th Dec 2021 at 17:58

Population Levels Assessment of the Distribution of Disease-Associated Variants With Emphasis on Armenians - A Machine Learning Approach.

LHA - Leipzig Health Atlas, oBIG - omics Bioinformatics for Health

Abstract (Expand)

Background: During the last decades a number of genome-wide association studies (GWASs) has identified numerous single nucleotide polymorphisms (SNPs) associated with different complex diseases. However, … associations reported in one population are often conflicting and did not replicate when studied in other populations. One of the reasons could be that most GWAS employ a case-control design in one or a limited number of populations, but little attention was paid to the global distribution of disease-associated alleles across different populations. Moreover, the majority of GWAS have been performed on selected European, African, and Chinese populations and the considerable number of populations remains understudied. Aim: We have investigated the global distribution of so far discovered disease-associated SNPs across worldwide populations of different ancestry and geographical regions with a special focus on the understudied population of Armenians. Data and Methods: We have used genotyping data from the Human Genome Diversity Project and of Armenian population and combined them with disease-associated SNP data taken from public repositories leading to a final dataset of 44,234 markers. Their frequency distribution across 1039 individuals from 53 populations was analyzed using self-organizing maps (SOM) machine learning. Our SOM portrayal approach reduces data dimensionality, clusters SNPs with similar frequency profiles and provides two-dimensional data images which enable visual evaluation of disease-associated SNPs landscapes among human populations. Results: We find that populations from Africa, Oceania, and America show specific patterns of minor allele frequencies of disease-associated SNPs, while populations from Europe, Middle East, Central South Asia, and Armenia mostly share similar patterns. Importantly, different sets of SNPs associated with common polygenic diseases, such as cancer, diabetes, neurodegeneration in populations from different geographic regions. Armenians are characterized by a set of SNPs that are distinct from other populations from the neighboring geographical regions. Conclusion: Genetic associations of diseases considerably vary across populations which necessitates health-related genotyping efforts especially for so far understudied populations. SOM portrayal represents novel promising methods in population genetic research with special strength in visualization-based comparison of SNP data.

Authors: M. Nikoghosyan, S. Hakobyan, A. Hovhannisyan, H. Loeffler-Wirth, H. Binder, A. Arakelyan

Date Published: 21st May 2019

Publication Type: Journal article

PubMed ID: 31105750

Citation: Front Genet. 2019 Apr 26;10:394. doi: 10.3389/fgene.2019.00394. eCollection 2019.

Created: 22nd Apr 2020 at 12:57, Last updated: 7th Dec 2021 at 17:58

Autoimmunity and autoinflammation: A systems view on signaling pathway dysregulation profiles.

LHA - Leipzig Health Atlas

Abstract (Expand)

INTRODUCTION: Autoinflammatory and autoimmune disorders are characterized by aberrant changes in innate and adaptive immunity that may lead from an initial inflammatory state to an organ specific damage. … These disorders possess heterogeneity in terms of affected organs and clinical phenotypes. However, despite the differences in etiology and phenotypic variations, they share genetic associations, treatment responses and clinical manifestations. The mechanisms involved in their initiation and development remain poorly understood, however the existence of some clear similarities between autoimmune and autoinflammatory disorders indicates variable degrees of interaction between immune-related mechanisms. METHODS: Our study aims at contributing to a holistic, pathway-centered view on the inflammatory condition of autoimmune and autoinflammatory diseases. We have evaluated similarities and specificities of pathway activity changes in twelve autoimmune and autoinflammatory disorders by performing meta-analysis of publicly available gene expression datasets generated from peripheral blood mononuclear cells, using a bioinformatics pipeline that integrates Self Organizing Maps and Pathway Signal Flow algorithms along with KEGG pathway topologies. RESULTS AND CONCLUSIONS: The results reveal that clinically divergent disease groups share common pathway perturbation profiles. We identified pathways, similarly perturbed in all the studied diseases, such as PI3K-Akt, Toll-like receptor, and NF-kappa B signaling, that serve as integrators of signals guiding immune cell polarization, migration, growth, survival and differentiation. Further, two clusters of diseases were identified based on specifically dysregulated pathways: one gathering mostly autoimmune and the other mainly autoinflammatory diseases. Cluster separation was driven not only by apparent involvement of pathways implicated in adaptive immunity in one case, and inflammation in the other, but also by processes not explicitly related to immune response, but rather representing various events related to the formation of specific pathophysiological environment. Thus, our data suggest that while all of the studied diseases are affected by activation of common inflammatory processes, disease-specific variations in their relative balance are also identified.

Authors: A. Arakelyan, L. Nersisyan, D. Poghosyan, L. Khondkaryan, A. Hakobyan, H. Loffler-Wirth, E. Melanitou, H. Binder

Date Published: 4th Nov 2017

Publication Type: Not specified

PubMed ID: 29099860

Citation: PLoS One. 2017 Nov 3;12(11):e0187572. doi: 10.1371/journal.pone.0187572. eCollection 2017.

Created: 22nd Apr 2020 at 13:42, Last updated: 7th Dec 2021 at 17:58

View all 20 items

T2DM Ontology

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

T2DM Phenotype Algorithm Specification Ontology (PASO) developed using PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 9th Mar 2020 at 15:52, Last updated: 12th Aug 2020 at 15:23

T2DM Tabular Representation

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

The tabular representation of the T2DM phenotype algorithm generated by PhenoMan using the T2DM ontology

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 9th Mar 2020 at 16:00, Last updated: 11th Aug 2020 at 14:14

T2DM Case 5 Reasoner Report

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 10th Mar 2020 at 12:00, Last updated: 10th Mar 2020 at 12:00

T2DM Case 4 Reasoner Report

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 10th Mar 2020 at 11:58, Last updated: 10th Mar 2020 at 11:58

T2DM Case 3 Reasoner Report

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 10th Mar 2020 at 11:57, Last updated: 10th Mar 2020 at 11:57

T2DM Case 2 Reasoner Report

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 10th Mar 2020 at 11:47, Last updated: 10th Mar 2020 at 11:47

T2DM Case 1 Reasoner Report

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

Example Reasoner Report generated by PhenoMan

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 10th Mar 2020 at 11:45, Last updated: 10th Mar 2020 at 11:45

T2DM Graphical Representation

LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare

The decision tree was generated by PhenoMan in GraphML format and was processed using an automatic layout of the yEd Graph Editor. Nonetheless, it is also possible to generate the complete tree as image in PNG format.

Creator: Alexandr Uciteli

Submitter: Alexandr Uciteli

Data file type: Not specified

Investigations: Ontology-based Phenotyping

Studies: Ontological Modelling of Type 2 Diabetes Mellit...

Resources: Ontological Modelling of T2DM Phenotype using P...

Download

Created: 9th Mar 2020 at 16:08, Last updated: 9th Mar 2020 at 16:08

2 hidden items

oposSOM Browser

LHA - Leipzig Health Atlas

oposSOM is a comprehensive, machine learning based open-source data analysis software combining functionalities such as diversity analyses, biomarker selection, function mining, and visualization. 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 ...

Creator: Henry Löffler-Wirth

Submitter: René Hänsel

Model type: Self-Organizing Map

Model format: R package

Environment: Shiny

Organism: Not specified

Human Disease: Not specified

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

Download

Created: 22nd Jun 2020 at 09:12, Last updated: 28th Jan 2022 at 15:21

PanCancer Browser

LHA - Leipzig Health Atlas

The PanCancer Browser is a web application for the interactive comparison of molecular landscapes of different cancers provided by the oposSOM analysis pipeline. It complements the single data set-centered browsing tool oposSOM-Browser.

Creator: Henry Löffler-Wirth

Submitter: Henry Löffler-Wirth

Model type: Self-Organizing Map

Model format: R package

Environment: Shiny

Organism: Not specified

Human Disease: Not specified

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

Created: 3rd Feb 2021 at 16:47, Last updated: 3rd Feb 2021 at 16:47

Core Ontology of Phenotypes

Onto-Med Research Group, LHA - Leipzig Health Atlas

(Show All)

Core Ontology of Phenotypes. Contribute to Onto-Med/COP development by creating an account on GitHub.

Creators: Heinrich Herre, Alexandr Uciteli, Christoph Beger

Submitter: Christoph Beger

Model type: Not specified

Model format: Not specified

Environment: Not specified

Organism: Not specified

Human Disease: Not specified

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

External Link

Created: 20th Mar 2020 at 09:29, Last updated: 20th Mar 2020 at 09:29

Abstract: The Leipzig Health Atlas – A Repository for Research Data and Models

LHA - Leipzig Health Atlas

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The publication of research results is part of good scientific practice and is increasingly ex-pected and demanded. The FAIR data principles of data sharing are an important guideline - even if medical data sharing makes it necessary to define access restrictions.

Creators: René Hänsel, Frank A. Meineke, Christoph Beger

Submitter: Christoph Beger

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 31st Jan 2020 at 12:19, Last updated: 31st Jan 2020 at 12:21

Poster: The Leipzig Health Atlas - A Repository for Research Data and Models

LHA - Leipzig Health Atlas

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The Leipzig Health Atlas (LHA) offers a platform for presentation and exchange of publications, (bio-) medical data, models and software tools from the field of health research. The LHA is based on the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable). Currently, more than 18 research consortia contribute data from the domains lymphoma, glioma, sepsis, hereditary colorectal and breast cancer, and others. Target groups are clinicians, epidemiologists, molecular geneticists, human ...

Creators: René Hänsel, Frank A. Meineke, Christoph Beger

Submitter: Christoph Beger

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 31st Jan 2020 at 12:20, Last updated: 31st Jan 2020 at 12:20

Poster: Der Leipzig Health Atlas

LHA - Leipzig Health Atlas

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The need to manage research data is recognised by the research community - sponsors, legislators, publishers expect and encourage good scientific practice, which not only includes archiving, but also the availability of research data and results in line with FAIR principles. The publication gives a brief overview of the Leipzig Health Atlas (LHA), which is a project for the presentation and exchange of a wide range of publications, (bio) medical data (e.g. clinical, epidemiological, molecular), ...

Creators: René Hänsel, Matthias Löbe, Sebastian Stäubert, Christoph Beger

Submitter: Christoph Beger

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 17th Sep 2019 at 08:54, Last updated: 19th Sep 2019 at 07:00

Abstract: Der Leipzig Health Atlas

LHA - Leipzig Health Atlas

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Creators: René Hänsel, Matthias Löbe, Sebastian Stäubert, Christoph Beger

Submitter: Christoph Beger

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 17th Sep 2019 at 08:52, Last updated: 17th Sep 2019 at 08:55

Ontological Modelling and Reasoning of Phenotypes

LHA - Leipzig Health Atlas, SMITH - Smart Medical Information Technology for Healthcare, Onto-Med Research Group

Presentation on JOWO/ODLS 2019 in Graz

Creators: Alexandr Uciteli, Christoph Beger

Submitter: Christoph Beger

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Created: 7th Sep 2020 at 10:07, Last updated: 7th Sep 2020 at 10:07

Christoph Beger

Projects: LHA - Leipzig Health Atlas, Onto-Med Research Group, SMITH - Smart Medical Information Technology for Healthcare, COVID-19 Leipzig, LIFE Child, LIFE - Leipzig Research Center for Civilization Diseases, Project Test Demonstrator

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universitätsklinikum Leipzig, AöR, invalid

https://orcid.org/0000-0002-1166-0368

Expertise: data integration, ruby, r, java, perl

LHA Data Portal Bot

Projects: LIFE - Leipzig Research Center for Civilization Diseases, LHA - Leipzig Health Atlas, GLA - German Lymphoma Alliance, SepNet - German Competence Network Sepsis

Institutions: University of Leipzig

René Hänsel

Projects: HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia, e:Med, CapSys - Systems Medicine of Community Acquired Pneumonia, LHA - Leipzig Health Atlas, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, LIFE Child, GLA - German Lymphoma Alliance, MMML-MYC-SYS, HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, MMML - Molecular mechanisms in malignant lymphoma, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, NLP4CR - Natural Language Processing for Clinical Research, LIFE Heart, ProstataCA, SepNet - German Competence Network Sepsis, Genetical Statistics and Systems Biology, GGN - German Glioma Network, COVID-19 Leipzig, SMITH - Smart Medical Information Technology for Healthcare, Management of health information systems, LivSys Transfer - Transfer of the LivSys in vitro system for hepatotoxicity into application, Project Test Demonstrator

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)

https://orcid.org/0000-0001-8344-0658

Roles: Technician

Expertise: Data Management, Data analysis, Python, Html

Admin Istrator

Projects: LHA - Leipzig Health Atlas

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)

Toralf Kirsten

Projects: LIFE - Leipzig Research Center for Civilization Diseases, LHA - Leipzig Health Atlas

Institutions: Interdisciplinary Center for Bioinformatics (IZBI), Faculty of Applied Computer and Biological Sciences, University of Applied Sciences Mittweida

https://orcid.org/0000-0001-7117-4268

Roles: Project Coordinator

Expertise: Record Linkage, Ontology Matching, Schema Matching, FAIR Data, data integration, data sharing

Tools: java, r, PPRL

Markus Löffler

Projects: Genetical Statistics and Systems Biology, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, GLA - German Lymphoma Alliance, LIFE HNC - Head and Neck Cancer Group, LIFE - Leipzig Research Center for Civilization Diseases, MMML-MYC-SYS, LIFE Adult, MMML - Molecular mechanisms in malignant lymphoma, SepNet - German Competence Network Sepsis, HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia, e:Med, SMITH - Smart Medical Information Technology for Healthcare, LHA - Leipzig Health Atlas, POLAR - Polypharmacy, Drug Interactions, Risks, COVID-19 Leipzig

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig

Prof. Dr. Markus Löffler Universität Leipzig Institut für Medizinische Informatik, Statistik und Epidemiologie Härtelstraße 16-18 04107 Leipzig

Henry Löffler-Wirth

Projects: Think different, imSAVAR - Immune safety avatar: nonclinical mimicking of the immune system effects of immunomodulatory therapies, oBIG - omics Bioinformatics for Health, GLA - German Lymphoma Alliance, MMML-MYC-SYS, Leipzig Melanoma Studies, GGN - German Glioma Network, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, COVID-19 Leipzig, LHA - Leipzig Health Atlas

Institutions: University of Leipzig, Interdisciplinary Center for Bioinformatics (IZBI)

https://orcid.org/0000-0001-8239-440X

Frank A. Meineke

Projects: LHA - Leipzig Health Atlas, SMITH - Smart Medical Information Technology for Healthcare, POLAR - Polypharmacy, Drug Interactions, Risks, Management of health information systems, Project Test Demonstrator

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)

https://orcid.org/0000-0002-9256-7543

Thomas Peschel

Projects: LHA - Leipzig Health Atlas, LIFE - Leipzig Research Center for Civilization Diseases, POLAR - Polypharmacy, Drug Interactions, Risks

Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)

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16th Leipzig Research Festival for Life Sciences

No description specified

Start Date: 30th Jan 2020

End Date: 30th Jan 2020

Event Website: https://conference.uni-leipzig.de/researchfestival/

Country: Germany

City: Leipzig

Created: 31st Jan 2020 at 12:15

„Forschungsdaten in Sachsen: Planen – Organisieren – Nachnutzen“ – 1. sächsische FDM-Tagung

The conference will focus on current contributions to research data management in Saxony. On the basis of practical reports and a poster session, it will be shown what research data management can achieve and what advantages it can offer. An advanced training course on data management planning will help to explore the possibilities and challenges of the FDM for oneself and for research projects. Finally, important aspects and questions will be discussed with each other and with experts at several ...

Start Date: 19th Sep 2019

End Date: 19th Sep 2019

Event Website: https://saxfdm.de/termin/erste-saechsische-tagung-zum-forschungsdatenmanagement/

Country: Germany

City: Dresden

Created: 17th Sep 2019 at 08:23

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