Data integration is often one of the first milestones on the long road to find a satisfying answer for an open question. Since data and knowledge in the life science are scattered over millions of publications and thousands of heterogeneous databases, their integration is still a major challenge for science and industry alike. The huge interest in the many aspects of life science data integration is documented by a number of recurring conferences and workshops, a fairly large body of literature and the constant development of new tools in this area. It is not always an easy task to keep track of the latest concepts, the most promising practices and the best tools to solve a given problem. In order to help this situation, the present special issue of Briefings in Bioinformatics is devoted to data and knowledge integration in the life sciences. The articles cover many different topics in this area ranging from biomedical literature mining over web services and workflows to the construction of a knowledge base for systems pathology and the integration of mouse-related data. Most of the knowledge available in the life sciences is not stored in databases but in many millions of scientific publications. The amount of literature published each year makes it extremely difficult to keep track of the latest results. The importance of being able to find and extract relevant knowledge from the huge amount of biomedical literature is documented in three articles which cover different aspects of this topic. The first of these articles is contributed by Jung-jae Kim et al. and reviews online services for seeking information in biomedical literature to facilitate improvements of practice. After that, Rainer Winnenburg and colleagues give an overview of the state of the art in text mining and discuss the combination of such approaches with manual curation efforts for annotation projects. In the third article, Pankaj Agarwal and David Searls give an industrial perspective on how literature mining is used to support drug discovery. The huge amounts of data that are now produced on a daily basis, as well as the Internet as a modern infrastructure for scientific exchange, have created new demands with respect to data accessibility in recent years. Web services have become a very important technique for the programmatic access to online data and tools. This special issue includes two articles about this topic. First Heinz Stockinger et al. survey popular approaches for web services in the context of biological sequence analysis and discuss syntactic and semantic data integration issues with multiple web services. Carol Goble and colleagues then argue that data integration workflows based on web services can be difficult to use. The state of the art and current challenges in process curation are described as a step towards a solution to these problems. The final two contributions to this special issue are concerned with tools and techniques for data and knowledge integration in specific application areas. Michael Holger et al. use diabetes as an example to present strategies for developing computer-accessible knowledge sources as a foundation for systems pathology. Following that, Damian Smedley and colleagues critically assess solutions for data integration in functional genomics and describe a case study for the integration of mouse-related data. In summary, this special issue gives a good overview of current trends in life science data and knowledge integration as well as detailed insights into some specific application areas. Given the lack of (properly used) standards and procedures as well as the abundance of tools and data formats, the presented articles are valuable assets to enable the reader to stay informed about the latest developments in this very important area of bioinformatics.

MOTIVATION: Assembling the relevant information needed to interpret the output from high-throughput, genome scale, experiments such as gene expression microarrays is challenging. Analysis reveals genes that show statistically significant changes in expression levels, but more information is needed to determine their biological relevance. The challenge is to bring these genes together with biological information distributed across hundreds of databases or buried in the scientific literature (millions of articles). Software tools are needed to automate this task which at present is labor-intensive and requires considerable informatics and biological expertise. RESULTS: This article describes ONDEX and how it can be applied to the task of interpreting gene expression results. ONDEX is a database system that combines the features of semantic database integration and text mining with methods for graph-based analysis. An overview of the ONDEX system is presented, concentrating on recently developed features for graph-based analysis and visualization. A case study is used to show how ONDEX can help to identify causal relationships between stress response genes and metabolic pathways from gene expression data. ONDEX also discovered functional annotations for most of the genes that emerged as significant in the microarray experiment, but were previously of unknown function.

In the light of the increasing number of biological databases, their integration is a fundamental prerequisite for answering complex biological questions. Database integration, therefore, is an important area of research in bioinformatics. Since most of the publicly available life science databases are still exclusively exchanged by means of proprietary flat files, database integration requires parsers for very different flat file formats. Unfortunately, the development and maintenance of database specific flat file parsers is a nontrivial and time-consuming task, which takes considerable effort in large-scale integration scenarios. This paper introduces heuristically based concepts for automatic structure extraction from life science database flat files. On the basis of these concepts the FlatEx prototype is developed for the automatic conversion of flat files into XML representations.

MOTIVATION: Due to the increasing number of molecular biological databases and the exponential growth of their contents, database integration is an important topic of research in bioinformatics. Existing approaches in this area have in common that considerable efforts are needed to provide integrated access to heterogeneous data sources. RESULTS: This article describes the LIMBO architecture as a light-weight approach to molecular biological database integration. By building systems upon this architecture, the efforts needed for database integration can be significantly lowered. AVAILABILITY: As an illustration of the principle usefulness of the underlying ideas, a prototypical implementation based upon the LIMBO architecture is described. This implementation is exclusively based on freely available open source components like the PostgreSQL database management system and the BioRuby project. Additional files and modified components are available upon request from the author.

Several hundred internet accessible life science databases with constantly growing contents and varying areas of specialization are publicly available via the internet. Database integration, consequently, is a fundamental prerequisite to be able to answer complex biological questions. Due to the presence of syntactic, schematic, and semantic heterogeneities, large scale database integration at present takes considerable efforts. As there is a growing apprehension of extensible markup language (XML) as a means for data exchange in the life sciences, this article focuses on the impact of XML technology on database integration in this area. In detail, a general architecture for ontology-driven data integration based on XML technology is introduced, which overcomes some of the traditional problems in this area. As a proof of concept, a prototypical implementation of this architecture based on a native XML database and an expert system shell is described for the realization of a real world integration scenario.

MOTIVATION: Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases. RESULTS: In this publication, principles and methods that were used to implement SEMEDA (Semantic Meta Database) are described. Database owners can use SEMEDA to provide semantically integrated access to their databases as well as to collaboratively edit and maintain ontologies and controlled vocabularies. Biologists can use SEMEDA to query the integrated databases in real time without having to know the structure or any technical details of the underlying databases. AVAILABILITY: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.

One of the main benefits of object orientation is the concept of inheritance which allows for the derivation of new types/classes from existing ones. Within commonly used object oriented languages, inheritance is usually directed to attributes and method signatures, only. Considering languages providing means for the specification of object life cycles, the concept of inheritance needs to be extended to be able to cover not only static but also behavioural aspects. The article introduces a set of requirements for the modeling and inheritance of object behaviour. Based on a short survey of existing work, a new approach is introduced which is suited to be used with a class of object oriented Petri nets.

In the area of complex system design even the use of high-level Petri nets extended with substitutional constructs often results in models difficult to understand, maintain and extend. These problems, as well as a not satisfactory support for reuse of components, stem from the absence of capabilities to build Petri net models out of encapsulated modules. In order to overcome these limitations more sophisticated modularization techniques are needed. The extension of Petri nets with object-oriented concepts is a promising approach in this area, as these concepts offer well experienced and largely approved modularization capabilities. The paper gives a short overview of already existing proposals extending Petri nets with object-oriented concepts, pointing out why most of them provide no solution to the above stated deficiencies. To overcome the limitations of existing proposals a novel approach is presented, namely 'object-oriented predicate/transition nets'. Their application to software engineering is shown ranging from object design to visual programming.