Autoscribe Launches New Website
News Oct 11, 2013
Autoscribe has launched a new combined UK and US website ( www.autoscribe.co.uk and www.autoscribeinformatics.com) to reflect the worldwide nature of Autoscribe’s business. With a fresher, cleaner look, much improved navigation, additional content and more downloads, the site features a new ‘market’ section which allows visitors to see at a glance the applications of information management systems in different market areas, as well as a more in depth view of the Business Solutions that are available.
Another new section is devoted to information on the unique configuration capabilities of the Matrix family of LIMS. The ‘OneTime configuration tools’ are the lynch pin of the Matrix Gemini LIMS, making it highly configurable, adaptable and flexible, within a standard product core. These tools are used to create the initial configuration at implementation and can be used subsequently by either Autoscribe or customers’ staff to further configure or re-configure the system to keep it in step with any changes to the laboratory workflow or business practices.
The new site also has a stronger focus on real-life uses of Autoscribe products, with more case studies, and a glimpse of some of Autoscribe’s clients. With agreement from many customers in place, a comprehensive program is under way to produce a whole series of new case studies to further illustrate the diversity of applications. These will be added to the new site as they are completed.
Computer bits are binary, with a value of 0 or 1. By contrast, neurons in the brain can have all kinds of different internal states, depending on the input that they received. This allows the brain to process information in a more energy-efficient manner than a computer. A new study hopes to bring the two closer together.
MIT researchers have developed a cryptographic system that could help neural networks identify promising drug candidates in massive pharmacological datasets, while keeping the data private. Secure computation done at such a massive scale could enable broad pooling of sensitive pharmacological data for predictive drug discovery.
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