We present an expansion of the popular open source Visualization Toolkit (VTK) to support the ingestion, processing, and display of informatics data. The result is a flexible, component-based pipeline framework for the integration and deployment of algorithms in the scientific and informatics fields. This project, code named "Titan", is one of the first efforts to address the unification of information and scientific visualization in a systematic fashion. The result includes a wide range of informatics-oriented functionality: database access, graph algorithms, graph layouts, views, charts, UI components and more. Further, the data distribution, parallel processing and client/server capabilities of VTK provide an excellent platform for scalable analysis.
We describe G-Space, a straightforward linear time layout algorithm that draws undirected graphs based purely on their
topological features. The algorithm is divided into two phases. The first phase is an embedding of the graph into a 2-D
plane using the graph-theoretical distances as coordinates. These coordinates are computed with the same process used
by HDE (High-Dimensional Embedding) algorithms. In our case we do a Low-Dimensional Embedding (LDE), and
directly map the graph distances into a two dimensional geometric space. The second phase is the resolution of the
many-to-one mappings that frequently occur within the low dimensional embedding. The resulting layout appears to
have advantages over existing methods: it can be computed rapidly, and it can be used to answer topological questions
quickly and intuitively.
Dramatic technological advances in the field of genomics have made it possible to sequence the complete genomes of many
different organisms. With this overwhelming amount of data at hand, biologists are now confronted with the challenge of
understanding the function of the many different elements of the genome. One of the best places to start gaining insight on
the mechanisms by which the genome controls an organism is the study of embryogenesis.
There are multiple and inter-related layers of information that must be established in order to understand how the
genome controls the formation of an organism. One is cell lineage which describes how patterns of cell division give rise
to different parts of an organism. Another is gene expression which describes when and where different genes are turned
on. Both of these data types can now be acquired using fluorescent laser-scanning (confocal or 2-photon) microscopy of
embryos tagged with fluorescent proteins to generate 3D movies of developing embryos. However, analyzing the wealth of
resulting images requires tools capable of interactively visualizing several different types of information as well as being
scalable to terabytes of data.
This paper describes how the combination of existing large data volume visualization and the new Titan information
visualization framework of the Visualization Toolkit (VTK) can be applied to the problem of studying the cell lineage of
an organism. In particular, by linking the visualization of spatial and temporal gene expression data with novel ways of
visualizing cell lineage data, users can study how the genome regulates different aspects of embryonic development.