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
Elsevier and ExactCure recently announced a collaboration to develop and offer to hospitals – without charge – drug-specific exposure models for 20 already approved medicines that are being tested as potential treatments for Covid-19.
With the world’s focus on the COVID-19 pandemic, LIMS providers are working to develop solutions tailored to assist in the testing and management of virus samples.
Researchers at Harvard Medical School (HMS) have released an open source drug discovery platform, VirtualFlow, that harnesses supercomputing power to screen potentially billions of small organic compound structures in parallel, in the hunt for promising new drug molecules.
When designing a component or system, where do you start? In days gone by, designers would literally go back to the drawing board, using their experience and expertise to develop a new concept.
Effective utilisation of computing tools is critical to both AI and HPC research, with recent projects in both fields highlighting the scientific benefit of carefully managing resources.
Advances in computer vision combined with AI computing are helping pathologists to more accurately identify subtypes of cancer - leading to better treatments for patients, explains Dan Ruderman.
