BN++ – A Biological Information System

Abstract

SummaryRecent years have seen an explosive growth in the amount of biochemical data available. Numerous databases have been established and are being used as an essential resource by biologists around the world. The sheer amount and heterogeneity of these data poses a major challenge: data integration and, based thereupon, the integrative analysis of these data. We present BN++, the biochemical network library, a powerful software package for integrating, analyzing, and visualizing biochemical data in the context of networks. BN++ is based on a comprehensive and extensible object model (BioCore), which has been implemented as a C++ framework, a Java class library, and a relational database. The C++ framework is used to efficiently import, integrate, and analyze the data, which is stored in a data warehouse. The Java-based viewer (BiNA) provides a powerful platform-independent visualization of the data using sophisticated graph layout algorithms. Currently, the data warehouse imports and integrates data from about a dozen important databases including, among others, sequence data, metabolic and regulatory networks, and protein interaction data. We illustrate the usefulness of BN++ with a few select example applications. Availability: BN++ is open source software available from our website at www.bnplusplus. org.

Network-based interactive navigation and analysis of large biological datasets

“…The interface to UniPAX and its predecessor BN++ [26] provide comprehensive information retrieval and data exploration functionality.…”

Detecting Dysregulated Processes and Pathways

“…We will revisit the idea of network inference in the context of cancer therapy (see Section 14.8). Finally, meta databases like STRING [52] or information systems like BN++ [53] or ONDEX [54] integrate existing databases and several data sources into large data warehouses. Besides resulting in a larger dataset, this approach has the advantage that, a confidence value can be assigned to each entry based on the frequency of its occurrence in the source databases.…”

Graph-based sequence annotation using a data integration approach

“…In addition to standard database approaches, graph and ontology oriented approaches are being used with increasing success. While some of these graph based frameworks can be found in commercial products such as VTT (Gopalacharyulu, et al, 2005), ChipInspector / Bibliosphere Pathway Edition (from Genomatix), Phylosopher (from Genedata), ExPlain (from BIOBASE) and PathwayStudio (Nikitin, et al, 2003) (from Ariadne Genomics), some non-commercial systems are also available free of charge such as PathSys (Baitaluk, et al, 2006), BN++ (Küntzer, et al, 2006) and the ONDEX system (Köhler, et al, 2006;. Several projects have also followed a similar approach using the principles established for the semantic web such as SWEDI (Post, et al, 2007) or BioDASH (Neumann and Quan, 2006).…”