June/July 2006

Different data, different analytical tools, different users. How can scientific computing cope with diversity in the life sciences? Tom Wilkie discovers that data pipelining and workflow technology offer new approaches

Felix Grant explores the applications for - and reasoning behind - pattern recognition

Commercial laboratories increasingly turn to less-skilled staff for their routine analyses, but also want to use and share their results in far more ways than in the past. The key to achieving these different goals lies in the software, writes Siân Harris

Andre Geim, director, Centre for Mesoscience and Nanotechnology, University of Manchester