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Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA--the Biological Network Analyzer--a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/.

Background Cancer is a disease of genome alterations that arise through the acquisition of multiple somatic DNA sequence mutations. Some of these mutations can be critical for the development of a tumor and can be useful to characterize tumor types or predict outcome. Description We have constructed an integrated biological information system termed the Roche Cancer Genome Database (RCGDB) combining different human mutation databases already publicly available. This data is further extended by hand-curated information from publications. The current version of the RCGDB provides a user-friendly graphical interface that gives access to the data in different ways: (1) Single interactive search by genes, samples, cell lines, diseases, as well as pathways, (2) batch searches for genes and cell lines, (3) customized searches for regularly occurring requests, and (4) an advanced query interface enabling the user to query for samples and mutations by various filter criteria. Conclusion The interfaces of the presented database enable the user to search and view mutations in an intuitive and straight-forward manner. The database is freely accessible at http://rcgdb.bioinf.uni-sb.de/MutomeWeb/ .

Freshwater lenses, as important resource for drinking water, are sensitive to climate changes and sea level rise. To simulate this impact on the groundwater systems, hydraulic subsurface models have to be designed. Geophysical techniques can provide information for generating realistic models. The aim of our work is to show how ground-penetrating radar (GPR) investigations can contribute to such hydrological simulations. In the pilot area, Borkum island, GPR was used to map the shape of the groundwater table (GWT) and to characterise the aquifer. In total, 20 km of constant offset (CO) profiles were measured with centre frequencies of 80 and 200 MHz. Wave velocities were determined by common midpoint (CMP) measurements and vertical radar profiling (VRP) in a monitoring well. The 80 MHz CO data show a clear reflection at the groundwater table, whereas the reflection is weaker for the 200 MHz data. After correcting the GPR water tables for the capillary rise, they are in good accordance with the pressure heads of the observation wells in the area. In the centre of the island, the groundwater table is found up to 3.5 m above sea level, however it is lower towards the coastline and marshland. Some local depressions are observed in the region of dune valleys and around pumping stations of the local water supplier. GPR also reveals details within the sediments and highly-permeable aeolian sands can be distinguished from less-permeable marine sediments. Further, a silt loam layer below the water table could be mapped on a large area. The reflection characteristics indicates scattered erosion channels in this layer that cause it to be an aquitard with some leakage. GPR provides a high resolution map of the groundwater table and insight into the stratigraphy of the sediments and their hydraulic properties. This is valuable complementary information to the observation of sparsely distributed monitoring wells as input to hydraulic simulation.