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Informatics In-Depth Focus 2018
In this In-Depth Focus: enabling research on understudied and unstudied targets, and using multi-omics data to detail drug responses in the human metabolic network.
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Informatics
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New machine learning algorithm uncovers time-delayed interactions in cells
Scientists have designed a new machine learning algorithm that uses time-series data to uncover underlying biological networks.
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Operetta CLS High-Content Analysis System
6 February 2018 | By PerkinElmer
Operetta CLS is a high-content cell analysis system featuring a unique combination of technologies to deliver high speed, sensitivity, and resolution...
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Mirror-image peptides of existing drugs provide longer-lasting therapeutic effects
Researchers have developed a new technology for creating more durable disease-fighting molecules which could lead to drugs with longer-lasting effects...
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Video: PerkinElmer signals lead discovery
Quickly gain new insights into chemical and biomolecular research data. Featuring guided search and analysis workflows and dynamic data visualisations.
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Chemical oscillators offer a new level of molecular control
Researchers have created chemical amplifiers and a chemical oscillator using a systematic method that has the potential to embed sophisticated circuit computation within molecular systems...
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Informatics infrastructure for public-private collaborations in neglected disease research
Efforts to develop new medicines for diseases of the developing world (DDW) have been somewhat fragmented in the past and progress has been limited, despite considerable investment. Public-private partnership (PPP) is becoming an essential model for research in neglected disease areas. However, collaboration on this scale presents unique challenges, some…
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Using bioinformatics sequence similarities to optimise repurposing activities
A significant amount of selectivity and potency data originating from screening of drug targets is generated each year and deposited in public databases. This can be exploited to accelerate drug discovery, in particular, for a variety of repurposing activities...
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Machine learning approaches as tools to accelerate drug discovery
Computational methods based on machine learning approaches are being introduced increasingly widely to screen the large number of molecules that have never participated in the drug discovery process, but which might have significant drug development potential. This article considers the latest advances in machine learning as applied to drug discovery...
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Informatics In-Depth Focus 2017
In this In-Depth Focus we look at using bioinformatics sequence similarities to optimise repurposing activities; informatics infrastructure in neglected disease research, and machine learning for accelerating drug discovery.
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Bioprinted veins reveal new drug diffusion details
A scientific collaboration has developed vascularised 3-D bioprinted liver tissue constructs, providing more precise drug toxicity testing...
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BenevolentAI hires new head of Cheminformatics from The Institute of Cancer Research
BenevolentAI announced today it has hired Dr Nathan Brown, as its new Head of Cheminformatics following the promotion of Mark Davies...
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New device detects tumour cells in blood
A team of researchers has patented a mobile device that can monitor cancer quickly, cheaply, effectively and noninvasively...
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New data network for Huntington’s disease research
The first data network for this research could also be the blueprint for similar data networks for research into other conditions...