Electron tomography, also known as ET, provides researchers with a tiny window on to the alien world of molecular biology.

The technology works by shooting electron beams through super-slim samples at different angles, producing data that can be pieced together to produce a three-dimensional structure. The technology is well suited to biological specimens such as chromosomes and viruses, providing nano-scale resolution for an all-new look at these target macromolecules.

To achieve such resolution, ET demands sophisticated reconstruction algorithms. Where iterative algebraic algorithms yield high quality reconstructions, they are computationally expensive and their use requires high performance techniques.

Nano-scale grid-powered reconstruction

Along with his colleagues, Román Bilbao-Castro of the University of Almería, in Spain, has developed a new approach to tomographic reconstruction, reducing the global problem into a number of independent sub-problems using grid computing. The team are evaluating their approach using the EGEE infrastructure.

“We have thoroughly analyzed the influence of the problem size and the parallelism grain,” says Bilbao-Castro. “Our results demonstrate that the grid is better suited for the large reconstructions currently needed in electron tomography.”