Currently, visualization techniques in the genetic field require a very important modeling phase in terms of resources. 2D based projections of traditional visualization techniques are rarely adapted to manage and process such huge mass of information. To overcome such limitation, we propose to use a new graph modeling technique. This, when used in conjunction with virtual reality technology, allows biologists to have a wide visibility and fluent exploration through several points of view and user interaction, thus enabling what we can call visual data mining of big scientific data. The general principle of our approach is to build a biological network model in the form of a graph with a spatial representation adapted to the visualization of biological networks in a virtual environment. The results show that the improvement of the node distribution algorithm allows a better and more intuitive visualization, compared to the equivalent two-dimensional visualization.

MOTIVATION: Biologists usually work with textual DNA sequences (succession of A, C, G and T). This representation allows biologists to study the syntax and other linguistic properties of DNA sequences. Nevertheless, such a linear coding offers only a local and a one-dimensional vision of the molecule. The 3D structure of DNA is known to be very important in many essential biological mechanisms. By using 3D conformation models, one is able to construct a 3D trajectory of a naked DNA molecule. From the various studies that we performed, it turned out that two very different textual DNA sequences could have similar 3D structures. RESULTS: In this article, we address a new research work on 3D pattern matching for DNA sequences. The aim of this work is to enhance conventional pattern matching analyses with 3D-augmented criteria. We have developed an algorithm, based on 3D trajectories, which compares angles formed by these trajectories and thus quantifies the difference between two 3D DNA sequences. This analysis performs from a global scale to al local one. AVAILABILITY: Available on request from the authors.

Many databases and software tools are available for biologists in order to have access to genomic information. In a SQL manner, our information system GenoMEDIA addresses the problem of integrating heterogeneous data-bases and software utilities within a generic distributed platform. Lysa increases the GenoMEDIA SQL interface by adding an interactive collaborative graphical environment. Upon a usual query on biological database, gigabytes of data could be returned to the users. The aim of Lysa, through the databall concept, a certain kind of data introspection and collaborative engine, is to allow groups of users to make semantic links in these huge amounts of data. The main point of this paper is the collaborative framework written for Lysa. This framework allows multiple users to work upon the same shared biological data. This was written in order to add the capabilities and the knowledge of multiple users in order to extract information of the huge mass of data coming from biological databases.

Many databases and software tools are currently available for accessing genomic data. In general, each tool uses a different type of data in exchange protocols, and usually they offer specific services. The presented system approach, named GenoMEDIA, addresses the problem of integrating these heterogeneous databases and software utilities within a generic distributed platform. GenoMEDIA provides two specific middleware, named Lydia and Antje, for this integration. Lydia offers facilities for working simultaneously with a variety of services and databases; Antje is designed to allow users to manage multiple heterogeneous remote databases in a uniform vision. The aim of this paper is to present GenoMEDIA and how heterogeneous databases and remote services are integrated, in particular how Antje was designed, implemented and tested with various genomic databases.