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Integrative Data Semantics through a Model-enabled Data Stewardship

Philipp Wegner, Sebastian Schaaf, Mischa Uebachs, Daniel Domingo-Fernández, Yasamin Salimi, Stephan Gebel, Astghik Sargsyan, Colin Birkenbihl, Stephan Springstubbe, Thomas Klockgether, Juliane Fluck, Martin Hofmann-Apitius (+2 others)
2022 Bioinformatics  
Motivation The importance of clinical data in understanding the pathophysiology of complex disorders has prompted the launch of multiple initiatives designed to generate patient-level data from various modalities. While these studies can reveal important findings relevant to the disease, each study captures different yet complementary aspects and modalities which, when combined, generate a more comprehensive picture of disease aetiology. However, achieving this requires a global integration of
more » ... ata across studies, which proves to be challenging given the lack of interoperability of cohort datasets. Results Here, we present the Data Steward Tool (DST), an application that allows for semi-automatic semantic integration of clinical data into ontologies and global data models and data standards. We demonstrate the applicability of the tool in the field of dementia research by establishing a Clinical Data Model (CDM) in this domain. The CDM currently consists of 277 common variables covering demographics (e.g. age and gender), diagnostics, neuropsychological tests, and biomarker measurements. The DST combined with this disease-specific data model shows how interoperability between multiple, heterogeneous dementia datasets can be achieved. Availability The DST source code and Docker images are respectively available at and Furthermore, the DST is hosted at Supplementary information Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btac375 pmid:35652780 pmcid:PMC9344835 fatcat:ehfcpvpflfbsdjmgqxx3gulwla

The COVID-19 Ontology

Astghik Sargsyan, Alpha Tom Kodamullil, Shounak Baksi, Johannes Darms, Sumit Madan, Stephan Gebel, Oliver Keminer, Geena Mariya Jose, Helena Balabin, Lauren Nicole DeLong, Manfred Kohler, Marc Jacobs (+1 others)
2020 Bioinformatics  
The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel coronavirus (SARS-CoV-2) entities. The ontology has a strong scope on chemical entities suited for drug repurposing, as this is a major target of ongoing COVID-19 therapeutic development. The ontology comprises 2.270
more » ... s of concepts and 38.987 axioms (2622 logical axioms and 2434 declaration axioms). It depicts the roles of molecular and cellular entities in virus-host interactions and in the virus life cycle, as well as a wide spectrum of medical and epidemiological concepts linked to COVID-19. The performance of the ontology has been tested on Medline and the COVID-19 corpus provided by the Allen Institute. COVID-19 Ontology is released under a Creative Commons 4.0 License and shared via The ontology is also deposited in BioPortal at
doi:10.1093/bioinformatics/btaa1057 pmid:33346828 pmcid:PMC7799333 fatcat:ttlpagxf6rar7e6au2hmvsw3o4

Use of Monitoring Approaches to Verify the Predictive Accuracy of the Modeling of Particle-Bound Solid Inputs to Surface Waters

Katharina Allion, Michael Gebel, Mario Uhlig, Stefan Halbfass, Stephan Bürger, Lisa Kiemle, Stephan Fuchs
2021 Water  
For particle-bound substances such as phosphorus, erosion is an important input pathway to surface waters. Therefore, knowledge of soil erosion by water and sediment inputs to water bodies at high spatial resolution is essential to derive mitigation measures at the regional scale. Models are used to calculate soil erosion and associated sediment inputs to estimate the resulting loads. However, validation of these models is often not sufficiently possible. In this study, sediment input was
more » ... d on a 10 × 10 m grid for a subcatchment of the Kraichbach river in Baden-Wuerttemberg (Germany). In parallel, large-volume samplers (LVS) were operated at the catchment outlet, which allowed a plausibility check of the modeled sediment inputs. The LVS produced long-term composite samples (2 to 4 weeks) over a period of 4 years. The comparison shows a very good agreement between the modeled and measured sediment loads. In addition, the monitoring concept of the LVS offers the possibility to identify the sources of the sediment inputs to the water body. In the case of the Kraichbach river, it was found that around 67% of the annual sediment load in the water body is contributed by rainfall events and up to 33% represents dry-weather load. This study shows that the modeling approaches for calculating the sediment input provide good results for the test area Kraichbach and the transfer for a German wide modeling will produce plausible values.
doi:10.3390/w13243649 fatcat:bpvzsoh5m5dhde5qoganwvtgtq

Proposal of an Architecture for Terminology Management in a Research Project

Sara Mora, Sumit Madan, Stephan Gebel, Mauro Giacomini
2020 Studies in Health Technology and Informatics  
Clinical and medical knowledge evolve and this causes changes in concepts and terms that describe them. The objective of this work is to formally present an ontology-based standard architecture that will be used in the scenario of neurodegeneration research to maintain terminologies and their relations updated and coherent over the time. The proposed structure is composed by three elements that will allow the user to do a list of operations on the terminology resources explicitly contemplated by the Common Terminology Service Release 2 (CTS2).
doi:10.3233/shti200447 pmid:32570664 fatcat:c4clc2cijvam5n4x2hhgzvx5zq

Behavioral and Neural Correlates of Cognitive-Motor Interference during Multitasking in Young and Old Adults

Hannah Bohle, Jérôme Rimpel, Gesche Schauenburg, Arnd Gebel, Christine Stelzel, Stephan Heinzel, Michael Rapp, Urs Granacher
2019 Neural Plasticity  
The concurrent performance of cognitive and postural tasks is particularly impaired in old adults and associated with an increased risk of falls. Biological aging of the cognitive and postural control system appears to be responsible for increased cognitive-motor interference effects. We examined neural and behavioral markers of motor-cognitive dual-task performance in young and old adults performing spatial one-back working memory single and dual tasks during semitandem stance. On the neural
more » ... vel, we used EEG to test for age-related modulations in the frequency domain related to cognitive-postural task load. Twenty-eight healthy young and 30 old adults participated in this study. The tasks included a postural single task, a cognitive-postural dual task, and a cognitive-postural triple task (cognitive dual-task with postural demands). Postural sway (i.e., total center of pressure displacements) was recorded in semistance position on an unstable surface that was placed on top of a force plate while performing cognitive tasks. Neural activation was recorded using a 64-channel mobile EEG system. EEG frequencies were attenuated by the baseline postural single-task condition and demarcated in nine Regions-of-Interest (ROIs), i.e., anterior, central, posterior, over the cortical midline, and both hemispheres. Our findings revealed impaired cognitive dual-task performance in old compared to young participants in the form of significantly lower cognitive performance in the triple-task condition. Furthermore, old adults compared with young adults showed significantly larger postural sway, especially in cognitive-postural task conditions. With respect to EEG frequencies, young compared to old participants showed significantly lower alpha-band activity in cognitive-cognitive-postural triple-task conditions compared with cognitive-postural dual tasks. In addition, with increasing task difficulty, we observed synchronized theta and delta frequencies, irrespective of age. Task-dependent alterations of the alpha frequency band were most pronounced over frontal and central ROIs, while alterations of the theta and delta frequency bands were found in frontal, central, and posterior ROIs. Theta and delta synchronization exhibited a decrease from anterior to posterior regions. For old adults, task difficulty was reflected by theta synchronization in the posterior ROI. For young adults, it was reflected by alpha desynchronization in bilateral anterior ROIs. In addition, we could not identify any effects of task difficulty and age on the beta frequency band. Our results shed light on age-related cognitive and postural declines and how they interact. Modulated alpha frequencies during high cognitive-postural task demands in young but not old adults might be reflective of a constrained neural adaptive potential in old adults. Future studies are needed to elucidate associations between the identified age-related performance decrements with task difficulty and changes in brain activity.
doi:10.1155/2019/9478656 pmid:31582967 pmcid:PMC6748191 fatcat:kkdfnu5shjdunmyp5adifczvya

Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases

Venkata Satagopam, Wei Gu, Serge Eifes, Piotr Gawron, Marek Ostaszewski, Stephan Gebel, Adriano Barbosa-Silva, Rudi Balling, Reinhard Schneider
2016 Big Data  
Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of
more » ... iomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services-tranSMART, a Galaxy Server, and a MINERVA platform-are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and diseaserelated mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data.
doi:10.1089/big.2015.0057 pmid:27441714 pmcid:PMC4932659 fatcat:n7fcnszchrhk5of3kvkmvvjbty

MINERVA—a platform for visualization and curation of molecular interaction networks

Piotr Gawron, Marek Ostaszewski, Venkata Satagopam, Stephan Gebel, Alexander Mazein, Michal Kuzma, Simone Zorzan, Fintan McGee, Benoît Otjacques, Rudi Balling, Reinhard Schneider
2016 npj Systems Biology and Applications  
Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will
more » ... usage of networkencoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab. We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories. Published in partnership with the Systems Biology Institute MINERVA-a platform for curation of molecular networks P Gawron et al
doi:10.1038/npjsba.2016.20 pmid:28725475 pmcid:PMC5516855 fatcat:6x6wl2ubnff2rhsll2wzk5qbii

Land Use Pollution Potential of Water Sources Along the Southern Coast of South Africa

Hanlie Malherbe, Michael Gebel, Stephan Pauleit, Carsten Lorz
2018 Change and Adaptation in Socio-Ecological Systems  
Since the 1990's, the groundwater quality along the southern coast of the Western Cape Province of South Africa has been affected by increasing land use activities. Groundwater resources have become increasingly important in terms of providing good quality water. Polluted coastal groundwater as a source of submarine groundwater discharge also affects the quality of coastal water. For this study, land use activities causing groundwater pollution and areas at particular risk were identified. An
more » ... sessment approach linking land use/land cover, groundwater and submarine groundwater discharge on a meso-scale was developed and the methods applied to two study regions along the southern coastal area. Dryland and irrigated crop cultivation, and urbanized areas are subject to a "high" and "very high" risk of groundwater nitrogen pollution. Application of fertilizer must be revised to ensure minimal effects on groundwater. Practice of agricultural activities at locations which are not suited to the environment's physical conditions must be reconsidered. Informal urban development may contribute to groundwater nitrogen pollution due to poor waste water disposal. Groundwater monitoring in areas at risk of nitrogen pollution is recommended. Land use activities in the submarine groundwater discharge contribution areas was not found to have major effects on coastal water.
doi:10.1515/cass-2018-0002 fatcat:aromdums3jbtvnhvc74aev6sxe

Community-driven roadmap for integrated disease maps

Marek Ostaszewski, Stephan Gebel, Inna Kuperstein, Alexander Mazein, Andrei Zinovyev, Ugur Dogrusoz, Jan Hasenauer, Ronan M T Fleming, Nicolas Le Novère, Piotr Gawron, Thomas Ligon, Anna Niarakis (+6 others)
2018 Briefings in Bioinformatics  
Stephan Gebel is a molecular biologist, focusing on disease-related molecular pathways.  ... 
doi:10.1093/bib/bby024 pmid:29688273 fatcat:evg6lluamfg2tn5ygblmxsznea

CTO: A Community-Based Clinical Trial Ontology and Its Applications in PubChemRDF and SCAIView

Asiyah Yu Lin, Stephan Gebel, Qingliang Leon Li, Sumit Madan, Johannes Darms, Evan Bolton, Barry Smith, Martin Hofmann-Apitius, Yongqun Oliver He, Alpha Tom Kodamullil
2020 International Conference on Biomedical Ontology  
Driven by the use cases of PubChemRDF and SCAIView, we have developed a first community-based clinical trial ontology (CTO) by following the OBO Foundry principles. CTO uses the Basic Formal Ontology (BFO) as the top level ontology and reuses many terms from existing ontologies. CTO has also defined many clinical trial-specific terms. The general CTO design pattern is based on the PICO framework together with two applications. First, the PubChemRDF use case demonstrates how a drug Gleevec is
more » ... ked to multiple clinical trials investigating Gleevec's related chemical compounds. Second, the SCAIView text mining engine shows how the use of CTO terms in its search algorithm can identify publications referring to COVID-19-related clinical trials. Future opportunities and challenges are discussed.
dblp:conf/icbo/LinGLMDBSHHK20 fatcat:hgr5ykk67newxatuie3ia7dluu

Towards the validation of a lung tumorigenesis model with mainstream cigarette smoke inhalation using the A/J mouse

Walter Stinn, An Berges, Kris Meurrens, Ansgar Buettner, Stephan Gebel, Rosemarie B. Lichtner, Kris Janssens, Emilija Veljkovic, Yang Xiang, Ewald Roemer, Hans-Juergen Haussmann
2013 Toxicology  
Transcriptome analysis was performed following the manufacturer's recommendation in the Affymetrix Gene Chip ® Expression Analysis Technical Manual (Santa Clara, CA) as previously specified (Gebel et  ...  A rapid recovery of acute smoke exposure effects on gene regulation has been observed in previous studies (Gebel et al., 2010; Haussmann et al., 2009) , and indeed the induction of cyp1a1 as the most  ... 
doi:10.1016/j.tox.2013.01.005 pmid:23357402 fatcat:cfvkyfjyfjghxo2qlqt7cqtb6y

Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders

Martin Hofmann-Apitius, Gordon Ball, Stephan Gebel, Shweta Bagewadi, Bernard de Bono, Reinhard Schneider, Matt Page, Alpha Kodamullil, Erfan Younesi, Christian Ebeling, Jesper Tegnér, Luc Canard
2015 International Journal of Molecular Sciences  
Since the decoding of the Human Genome, techniques from bioinformatics, statistics, and machine learning have been instrumental in uncovering patterns in increasing amounts and types of different data produced by technical profiling technologies applied to clinical samples, animal models, and cellular systems. Yet, progress on unravelling biological mechanisms, causally driving diseases, has been limited, in part due to the inherent complexity of biological systems. Whereas we have witnessed
more » ... gress in the areas of cancer, cardiovascular and metabolic diseases, the area of neurodegenerative diseases has proved to be very challenging. This is in part because the aetiology of neurodegenerative diseases such as Alzheimer´s disease or Parkinson´s disease is unknown, rendering it very difficult to discern early causal events. Here we describe a panel of bioinformatics and modeling approaches that have recently been developed to identify candidate mechanisms of neurodegenerative diseases based on publicly available data and knowledge. We identify two complementary strategies-data mining techniques using genetic data as a starting point to be further enriched using other data-types, or alternatively to encode prior knowledge about disease mechanisms in a model based framework supporting reasoning and enrichment analysis. Our review illustrates the challenges entailed in integrating heterogeneous, multiscale and multimodal information in the area of neurology in general and neurodegeneration in particular. We conclude, that progress would be accelerated by increasing efforts on performing systematic collection of multiple data-types over time from each individual suffering from neurodegenerative disease. The work presented here has been driven by project AETIONOMY; a project funded Int.
doi:10.3390/ijms161226148 pmid:26690135 pmcid:PMC4691095 fatcat:son7r6tkxfgfvfe6apxejr3p24

Discovery of Emphysema Relevant Molecular Networks from an A/J Mouse Inhalation Study Using Reverse Engineering and Forward Simulation (REFS™)

Yang Xiang, Ulrike Kogel, Stephan Gebel, Michael J. Peck, Manuel C. Peitsch, Viatcheslav R. Akmaev, Julia Hoeng
2014 Gene Regulation and Systems Biology  
Chronic obstructive pulmonary disease (COPD) is a respiratory disorder caused by extended exposure of the airways to noxious stimuli, principally cigarette smoke (CS). The mechanisms through which COPD develops are not fully understood, though it is believed that the disease process includes a genetic component, as not all smokers develop COPD. To investigate the mechanisms that lead to the development of COPD/emphysema, we measured whole genome gene expression and several COPD-relevant
more » ... al endpoints in mouse lung tissue after exposure to two CS doses for various lengths of time. A novel and powerful method, reverse engineering and forward Simulation (refS™), was employed to identify key molecular drivers by integrating the gene expression data and four measured COPD-relevant endpoints (matrix metalloproteinase (MMP) activity, MMP-9 levels, tissue inhibitor of metalloproteinase-1 levels and lung weight). An ensemble of molecular networks was generated using refS™, and simulations showed that it could successfully recover the measured experimental data for gene expression and COPD-relevant endpoints. The ensemble of networks was then employed to simulate thousands of in silico gene knockdown experiments. Thirty-three molecular key drivers for the above four COPD-relevant endpoints were therefore identified, with the majority shown to be enriched in inflammation and COPD. KeywOrDs : Bayesian network, chronic obstructive pulmonary disease (COPD), reverse engineering and forward simulation (refS™) CItAtIoN: Xiang et al. discovery of emphysema Relevant molecular networks from an a/J mouse inhalation Study using Reverse engineering and Forward Simulation (ReFS™). Gene Regulation and Systems Biology 2014:8 45-61
doi:10.4137/grsb.s13140 pmid:24596455 pmcid:PMC3937248 fatcat:pt7tcxfnu5fhjehl6nczevdqhy

Linking Primary and Secondary Care after Psychiatric Hospitalization: Comparison between Transitional Case Management Setting and Routine Care for Common Mental Disorders

Charles Bonsack, Philippe Golay, Silvia Gibellini Manetti, Sophia Gebel, Pascale Ferrari, Christine Besse, Jérome Favrod, Stéphane Morandi
2016 Frontiers in Psychiatry  
Objectives: To improve engagement with care and prevent psychiatric readmission, a transitional case management intervention has been established to link with primary and secondary care. The intervention begins during hospitalization and ends 1 month after discharge. The goal of this study was to assess the effectiveness of this short intervention in terms of the level of engagement with outpatient care and the rate of readmissions during 1 year after discharge. Methods: Individuals
more » ... with common mental disorders were randomly assigned to be discharged to routine follow-up by private psychiatrists or general practitioners with (n = 51) or without (n = 51) the addition of a transitional case management intervention. Main outcome measures were number of contacts with outpatient care and rate of readmission during 12 months after discharge. results: Transitional case management patients reported more contacts with care service in the period between 1 and 3 months after discharge (p = 0.004). Later after discharge (3-12 months), no significant differences of number of contacts remained. The transitional case management intervention had no statistically significant beneficial impact on the rate of readmission (hazard ratio = 0.585, p = 0.114). conclusion: The focus on follow-up after discharge during hospitalization leads to an increased short-term rate of engagement with ambulatory care despite no differences between the two groups after 3 months of follow-up. This short transitional intervention did, however, not significantly reduce the rate of readmissions during the first year following discharge. Trial registration number: Identifier NCT02258737.
doi:10.3389/fpsyt.2016.00096 pmid:27313547 pmcid:PMC4889580 fatcat:kenfdhr67ban3oyg5wfq5dfbvm

The Kinetics of Transcriptomic Changes Induced by Cigarette Smoke in Rat Lungs Reveals a Specific Program of Defense, Inflammation, and Circadian Clock Gene Expression

Stephan Gebel, Bernhard Gerstmayer, Peter Kuhl, Jürgen Borlak, Kris Meurrens, Thomas Müller
2006 Toxicological Sciences  
Finally, the expression of arginase 1 may pertain to the 428 GEBEL ET AL.  ...  The validity of the microarray studies was further checked for 424 GEBEL ET AL.  ... 
doi:10.1093/toxsci/kfl071 pmid:16870687 fatcat:teap2vrehzhd5o5yodqxesmt2u
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