All Big Data articles – Page 3
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ArticleAn industry leader’s perspective on the complexity of scientific data
In this article, Dr Raminderpal Singh speaks to Janette Thomas of Five Alarm Bio for a biotech CEO’s perspective on the complexity of data faced by both large and small biotechs. Janette is on a mission to develop drugs targeting the chronic diseases associated with ageing. She shares her insights ...
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NewsUnexpected patterns in DNA mutations identified
Disruptions in TP53 and RB1 are key influencers that cause changes in the risk of mutations across chromosomes.
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NewsPromising strategy for glaucoma cell replacement therapy
Changing blood stem cells into retinal ganglion cells that can migrate to the eye’s retina offers hope for cell replacement therapy.
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ArticleDevelopments in trapped ion mobility spectrometry
Torsten Müller from Bruker Daltonics shares how trapped ion mobility spectrometry (TIMS) fundamentally improves immunopeptidomics research and addresses key challenges in this rapidly expanding field.
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ArticleEpisode 20- Regulations on artificial intelligence- impact on drug discovery
Tune in to this episode to hear experts discussing the hot topic that is AI and how AI technology is used in drug discovery, looking specifically at how Biotechs & Pharma are trying to keep up with emerging technology.
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ArticleLatest in lab automation
In this article Drug Target Review's Izzy Wood highlights three of the latest findings using lab automation techniques and technologies that aid scientists.
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ArticleArtificial intelligence: a great crash of hype into reality
Technology is infamous for falling into a hype cycle, with its peaks and valleys of exaggerated expectations and disillusionment — AI-driven drug discovery is no exception. In this article, Aaron Daugherty, Vice President Discovery at Aria Pharmaceuticals, highlights how the industry can use AI to transform research.
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NewsComputer models determine drug candidate’s ability to bind to proteins
Research by University of Arkansas scientists into the binding affinity of potential drugs could help reduce the cost and time associated with developing new drugs.
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