Prof. Dr. Falk Schreiber

• bioinformatics, medical informatics, systems biology
• network analysis, efficient graph algorithms
• information and scientific visualisation, visual computing
• information systems, databases, data mining
• mathematical modelling, simulation

My research focuses on two areas: the representation, modelling, analysis, and visualisation of biological networks in their spatial and temporal embedding; and visualisation and visual analytics of multimodal, multidimensional as well as network-related data. Goal of these research activities is to support the knowledge generation process in the life sciences. As coordinator of the Bioinformatics research of the IPK Gatersleben, one of the major plant research institutes in Germany, I am particularly interested in plant bioinformatics and plant systems biology. However, I also have close collaboration with scientists from several other fields, especially medicine.
For an integrative, systems biology directed approach it is not sufficient to consider the biological entities (such as DNA, RNA, proteins, metabolites) alone but is necessary to study their interactions and link the data from experimental groups to relevant processes and networks (such as regulatory, interactomics, and metabolic networks). These networks are embedded in spatial (from cellular compartments to tissues and organs) and temporal (from enzymatic reactions to developmental processes to evolution of networks) environments.
Therefore I research and develop algorithms, methods and systems in areas such as databases and information systems (to represent networks as well as diverse high-throughput data), data integration and data mining (to combine complex data and networks and derive knowledge from the data), visualisation, visual analytics and image processing (to help explore and analyse the data/images/networks in 2D to 4D), network analysis (to support hypothesis building), and mathematical modelling and simulation (to evaluate processes and support in silico predictions). I am interested in theoretical and practical problems from computer science and bioinformatics as well as in the underlying biological and medical questions.
Detailed descriptions of current research projects can be found on the project page of my research group.

I have taught computer science and bioinformatics courses at undergraduate and postgraduate levels at the University of Passau (Germany), The University of Sydney (Australia), the University of Dortmund (Germany), the University of Kiel (Germany) and the University of Halle (Germany).

• Google Scholar
• DBLP Bibliography Server
• CiteSeer
• PubMed

I have developed/managed the development of several software tools. Major freely available tools are listed below.

Visualisation and analysis of networks containing experimental data
VANTED is a tool for visual exploration and statistical analysis of complex biochemical data sets. For this task it is necessary to integrate and process data from different areas of genome, proteome and metabolome research and to present the results in a user-friendly way. The emphasis is on the linkage of experimental data with metabolic and regulatory networks under consideration of their spatial (3D) and temporal embedding as well as on network analysis and simulation algorithms. VANTED allows to load and edit biological networks, to map experimental data sets onto the network elements, to visualise and analyse time series data or data of different genotypes or organisms in the network context, to combine *omics and network information with spatial (2D and 3D) content such as NMR images and to apply several analysis methods to the combined data. Several add-ons extend VANTED.

Managing crop plant metabolic pathways and models
MetaCrop is a manually curated repository of high quality information concerning the metabolism of crop plants. This includes pathway diagrams, reactions, locations, transport processes, reaction kinetics, taxonomy and literature. MetaCrop provides detailed information on seven major crop plants and initial information about several other plants. The web interface supports an easy exploration of the information from overview pathways to single reactions. It also allows model creation and automatic data export for detailed models of metabolic pathways therefore supporting systems biology approaches. MetaCrop is a collaborative project with the IPK research group Bioinformatics and is based on the Meta-All system.

Editing, processing and visualisation of KGML pathway files
KGML-ED allows the dynamic exploration and editing of KEGG Pathway diagrams. It is a graphical network editor, that provides read- and write-support for the KGML (KEGG Markup Language) file format. Pathway files are loaded and transformed into a graph which may be modified to fulfill user-specific needs and explored with network exploration approaches.

Analysing centralities in biological networks
The ranking of network elements using centralities is one method to analyse network structured data and help to uncover important properties of networks, and CentiBiN is a tool to assist the centrality based analysis of networks. It supports computation and comparison of different network centralities and is used in our ongoing work on evaluating centrality measures for specific biological networks.

Motifs in networks
Motifs (patterns) in networks may represent building blocks of functional modules that carry out a relatively distinct function in biological networks, and MAVisto is a framework for their analysis. It contains algorithms to recognise multiple appearances of motifs in the target network under different frequency concepts, a motif preserving layout algorithm, and navigation techniques to explore the underlying structure of the network given by the motifs.