ePlant and the 3D Data Display Initiative: Integrative Systems Biology on the World Wide Web

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed “ePlant” (http://bar.utoronto.ca/eplant) – a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the “3D Data Display Initiative” (http://3ddi.org)

Energy-based Error Control Strategies Suitable for Long MD Simulations

When evaluating integration schemes used in molecular dynamics (MD) simulations, energy conservation is often cited as the primary criterion by which the integrators should be com- pared. As a result variable stepsize Runge-Kutta methods are often ruled out of consideration due to their characteristic energy drift. We have shown that by appropriately modifying the stepsize selection strategy in a variable stepsize RK method it is possible for the MD practitioner to obtain substantial control over the energy drift during the course of a simulation. This ability has been previously unreported in the literature, and we present numerical examples to illustrate that it can be achieved without sacrificing computational efficiency under currently obtainable timescales.MAS