Homepage: TRR-54

Funding: Deutsche Forschungsgemeinschaft

Period: 2009 - 2011 (first funding period)

Project partner: See this list

A short description of the overall goals of the Transregio can be found here (in German)

The goal of subproject Z3 is to develop and maintain a comprehensive data management and analysis platform for the Transregio. The platform will be based on a central database for storing experimental data as produced in the other subprojects. All data will undergo a standardized preprocessing stage and will be reviewed with respect to defined quality criteria. We database will also link the experimental data with information that is integrated from external data sources. It will be accessible through an intuitive web interface that also includes customizable functionality for integrated data analysis and visualization. Thus, the project will help to build up a high-quality, comprehensive data set offering an optimal basis for subsequent studies.

Homepage:ColoNET

Funding: Bundesministerium für Bildung und Forschung

Period: 2009 - 2012

Project partner: Charite Berlin, Institute for Theoretical Biology, HUB, MDC Berlin, DKFZ Heidelberg, Universität Potsdam, Universität Saarbrücken, Universität Halle, MicroDiscovery GmbH

Our project will develop a software for ranking potential biomarkers with respect to their diagnostic power for colorectal carcinoma. The ranking will be based on information extracted from scientific articles, models of the important pathways as created by other projects within ColoNet, experimental results and data integrated from public sources. All information will be filtered through a rigorous quality control and will be weighted based on the strength of their respective evidence.Furthermore, the project will provide support for searching and analyzing the relevant literature using text mining methods.

Homepage: METRIK

Funding: Deutsche Forschungsgemeinschaft

Period: 2006-2010 (first funding period)

Project partner: See this list

Recent progress in basic research has lead to visions how to use new self-organizing networks for advanced information systems. These networks function without central administration – all nodes are able to adapt themselves to new environments autonomously and independently. The addition of new nodes or failure of individual nodes does not significantly impact the network’s ability to function properly. Information systems and underlying technologies for self-organizing networks, in the context of a specific application domain, are the central topic of research for this graduate school. The research focuses on the important technologies needed at each individual node of a self-organizing network. Research challenges within this graduate school include: finding a path through a network with the help of new routing protocols and forwarding techniques, replication of decentralized data, automated deployment and update of software components at runtime as well as work-load balancing among terminal devices with limited resources. Furthermore, non-functional aspects such as reliability, latency and robustness will be studied.

Homepage: AliBaba (Java Web Start Application)

Funding: Bundesministerium für Bildung und Forschung (BCB), Max Planck Society

Period: 2002 -

Project partner:

The extraction of interactions taking place between various biological objects from text has become a major point of research for text mining during the last years. Our group focuses on the collection of interaction networks, both to provide quick overviews over specified subparts of domains, and to build complete interaction graphs that can be queried afterwards. We put our current emphasis on mining protein-protein interactions from scientific publications.

Homepage:

Funding: Bundesministerium für Bildung und Forschung (BCB)

Period: 2005 -

Project partner:

Graphs are playing an increasingly important role in many areas of biology. Examples are metabolic networks, networks of gene regulation, graphs formed of protein-protein interactions and complexes, and cascades in signal transduction. The size of the graphs under study have, due to improved experimental techniques, considerably grown in size, with many networks today reaching tens of thousands of nodes. In our project, we develop algorithms and systems for efficiently handling graphs of such sizes. In particular, we study graph-based query languages, indexing, cluster-based analysis and visualization.

Homepage: Aladin

Funding: Bundesministerium für Bildung und Forschung (Leser), Deutsche Forschungsgemeinschaft (Naumann)

Period: 2005 -

Project partner: Felix Naumann, Hasso-Plattner Institute Potsdam

Aladin aims - as Columba - on integration of databases in the life sciences. But opposed to Columba, Aladin's challenge is to integrate the data sources automatically. The fundamental idea is to work data-centric instead of schema-centric, which is besides its known disadvantages especially unsuitable for life science databases. Another major point for Aladin is to use domain-specific knowledge for integration strategies, e.g. common properties and structures of life science databases.