The development of LIMS will involve not only integrated data, but integration with enterprise applications, in Kevin Smith's view
We must move beyond software designed to solve single physics problems, according to Lars Langemyr
Clare Sansom talks to Janet Thornton, a pioneer of computing for the life sciences
Conrad Wolfram believes we should treat computers like cars: we should specify the problem and let the computer do the working out
Tom Wilkie looks at 10 years of scientific computing
Web services will offer a way for LIMS to integrate with enterprise resource planning systems, says Peter Rees
Rohit Khanna looks forward to the integration of instruments and software to master the mounds of data created in the lab
Dr John McAlister finds that scientific computing is not an end in itself but that success depends on it
Susie Stephens and Dennis Constantinou see Grid computing as the way to master the flood of information from the life sciences
Jack Little believes that model-based design is the best way to turn new ideas into real things
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.
