Towards a Mechanism-Based Taxonomy of Alzheimer’s Disease: Modeling and Mining Strategies for the Identification of Complex Pathophysiology Underlying Neurodegenerative Diseases

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Towards a Mechanism-Based Taxonomy of Alzheimer’s Disease:

Modeling and Mining Strategies for the Identification of Complex Pathophysiology Underlying Neurodegenerative Diseases

Webinar – November 21, 2014 at 12pm ET

By Martin Hofman-Apitius, PhD, Department Head of Bioinformatics at Fraunhofer Institute for Algorithims and Scientific Computing (SCAI); Alpha Tom Kodamullil, PhD candidate, researcher at Fraunhofer SCAI; Shweta Bagewadi, PhD candidate, researcher at Fraunhofer SCAI

This webinar featured Dr. Martin Hofmann-Apitius, Alpha Tom Kodamullil, and Shweta Bagewadi from the Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) in Sankt Augustin, Germany.  Together, they discussed the topic,“Towards a Mechanism-based Taxonomy of Alzheimer´s Disease: Modelling and Mining Strategies for the Identification of Complex Pathophysiology Underlying Neurodegenerative Diseases.”Fraunhofer SCAI, a governmental non-profit research institute, is the academic coordinator for the Innovative Medicines Initiative project AETIONOMY, which aims to generate a “mechanism-based taxonomy” for neurodegenerative diseases. This taxonomy will enable the classification of diseases based on mechanisms and facilitate patient subgroup stratification. To address challenges in developing a mechanism-based taxonomy from a single, comprehensive data set, researchers at Fraunhofer SCAI have employed two modelling approaches. These involve the systematic capturing of data and the formal representation of the relevant knowledge, as well as the integration of both data and knowledge. These modelling approaches are based on (1) OpenBEL, the open-source version of the “biological expression language” (www.openbel.org) and (2) NeuroRDF, an RDF-based framework. In this webinar, the presenters will discuss these modelling approaches and present mining strategies based on the models generated, while providing examples of the identification of biomarker candidates and candidate mechanisms for Alzheimer´s disease.

Martin Hofmann-Apitius holds a PhD in molecular biology and has worked for more than 10 years in experimental molecular biology. Since 2002, Dr. Hofmann-Apitius has been the head of the Department of Bioinformatics at the Fraunhofer SCAI, and is also a professor of Applied Life Science Informatics at Bonn-Aachen International Center for Information Technology, as well as the initiator and academic coordinator for the IMI project AETIONOMY.

Alpha Tom Kodamullil, who received a master’s degree in Life Science Informatics from the University of Bonn, is currently a PhD student at Bonn as well as a researcher at Fraunhofer SCAI. Her research work mainly focuses on automatic expansion of computable disease models by developing reasoners.

Shweta Bagewadi is also pursuing a doctoral degree at the University of Bonn while conducting research at Fraunhofer SCAI, where her primary interest is in the field of neurodegeneration.