Michaela Gündel

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BACKGROUND Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases(More)
BACKGROUND The advent of Systems Biology has been accompanied by the blooming of pathway databases. Currently pathways are defined generically with respect to the organ or cell type where a reaction takes place. The cell type specificity of the reactions is the foundation of immunological research, and capturing this specificity is of paramount importance(More)
Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of 'big data' research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve(More)
BACKGROUND Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of models. Hindering these initiatives is a lack of a comprehensive ontology that covers the essential concepts of the simulation domain. RESULTS We(More)
We present a Knowledge Management System aimed at supporting collaborative research among participants in DC-THERA (" Dendritic Cells & Novel Immunothera-pies "), a European Network of Excellence (NoE) in the field of dendritic cells and novel immuno-therapies for cancer and infectious diseases. The DC-THERA Directory is intended to support a range of(More)
Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson’s disease. In the area of Parkinson’s research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies(More)
BACKGROUND In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). METHODS The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and(More)
Molecular signaling pathways have been long used to demonstrate interactions among upstream causal molecules and downstream biological effects. They show the signal flow between cell compartments, the majority of which are represented as cartoons. These are often drawn manually by scanning through the literature, which is time-consuming, static, and(More)
Neurodegenerative as well as autoimmune diseases have unclear aetiologies, but an increasing number of evidences report for a combination of genetic and epigenetic alterations that predispose for the development of disease. This review examines the major milestones in epigenetics research in the context of diseases and various computational approaches(More)
Formal biomedical ontologies offer the capability to retrieve domain-specific knowledge. Particularly for grievous diseases like Alzheimer's where latency of onset to clinical symptoms takes many years, automated structured mining approaches can generate great value. No single system is currently capable of covering a complete domain of Alz-heimer's disease(More)