BioAscent, Selcia Collaboration Enhances Online Collection
News Aug 02, 2016
BioAscent Discovery and Selcia have entered into an agreement to make Selcia’s unique compound fragment library available to researchers through BioAscent’s new online Compound Cloud service. The new agreement adds to the 125,000+ compounds available through Compound Cloud and stored at BioAscent’s state-of-the-art compound management and logistics facility. Scientists can now benefit from immediate access to Selcia’s 1366 fragment collection, which has been designed in collaboration with Cambridge MedChem Consulting. The collection contains a structurally-diverse range of compounds with little overlap with other commercially-available libraries consisting of both commercial and non-commercial custom synthesised fragments. All have been put through a stringent quality control process to ensure chemical attractiveness and stability. Customers can order ready-to-use, single-use sets for rapid despatch through Compound Cloud.
Compound Cloud promises to significantly enhance early-stage drug discovery, by enabling easy online selection and ordering of a diverse collection of IP-free, high quality chemicals for screening, including an increasing number of third party collections. It applies the cloud-computing concept to early stage drug discovery by enabling scientists to remotely pick and choose specific compounds of interest from BioAscent’s storage facility and have them quickly prepared and delivered for immediate use. By removing the need for organisations to expend resources in developing or acquiring compound collections, compound screening through Compound Cloud becomes highly cost- and time-efficient.
Analytical Tool Predicts Disease-Causing GenesNews
Predicting genes that can cause disease due to the production of truncated or altered proteins that take on a new or different function, rather than those that lose their function, is now possible thanks to an international team of researchers that has developed a new analytical tool to effectively and efficiently predict such candidate genes.
Researchers Move Closer to Completely Optical Artificial Neural NetworkNews
Researchers have shown that it is possible to train artificial neural networks directly on an optical chip. The significant breakthrough demonstrates that an optical circuit can perform a critical function of an electronics-based artificial neural network and could lead to less expensive, faster and more energy efficient ways to perform complex tasks such as speech or image recognition.
Kidney Cancer Driver Could Lead to New Treatment StrategyNews
Scientists have uncovered a potential therapeutic target for kidney cancers that have a common genetic change. Scientists have known this genetic change can lead to an overabundance of blood vessels, which help feed nutrients to the tumors. Their latest finding shows a potential new cancer-driving pathway.READ MORE