Københavns Universitets Videoportal web@adm.ku.dk https://ku.23video.com da-dk Visualplatform http://blogs.law.harvard.edu/tech/rss Københavns Universitets Videoportal episodic no https://ku.23video.com/files/rv1.9/sitelogo.gif https://ku.23video.com http://video.ku.dk/photo/75750751/how-do-we-use-machine-learning-in <p>Are you interested in how biology, maths and computer science can work together to solve the world's biggest problems? In this video I'll walk you through how we can use machine learning to analyse biological data called omics to understand any living system, explaining the concepts along the way.</p> <p>For further info and some more examples visit our website: <a href="https://www.findingpheno.eu/video2">https://www.findingpheno.eu/video2</a></p><p><a href="http://video.ku.dk/photo/75750751/how-do-we-use-machine-learning-in"><img src="http://video.ku.dk/64968577/75750751/2668df96ec61ec1b9baf78f6f0e9d375/standard/download-10-thumbnail.jpg" width="75" height=""/></a></p> http://video.ku.dk/photo/75750751 Wed, 11 May 2022 11:45:11 GMT How Do We Use Machine Learning in Biology? Student video by FindingPheno.mp4 Are you interested in how biology, maths and computer science can work together to solve the world's biggest problems? In this video I'll walk you through how we can use machine learning to analyse biological data called omics to understand any living system, explaining the concepts along the way. For further info and some more examples visit our website: https://www.findingpheno.eu/video2 Are you interested in how biology, maths and computer science can work together to solve the world's biggest problems? In this video I'll walk you through how we can use machine learning to analyse biological data called omics to understand any... Københavns Universitets Videoportal 03:13 <p>Are you interested in how biology, maths and computer science can work together to solve the world's biggest problems? In this video I'll walk you through how we can use machine learning to analyse biological data called omics to understand any living system, explaining the concepts along the way.</p> <p>For further info and some more examples visit our website: <a href="https://www.findingpheno.eu/video2">https://www.findingpheno.eu/video2</a></p><p><a href="http://video.ku.dk/photo/75750751/how-do-we-use-machine-learning-in"><img src="http://video.ku.dk/64968577/75750751/2668df96ec61ec1b9baf78f6f0e9d375/standard/download-10-thumbnail.jpg" width="75" height=""/></a></p> big data biological data biological systems biology center for evolutionary hologenomics communication computer science data FindingPheno health Hologenomics machine learning mathematics omics outreach student teaching video http://video.ku.dk/photo/75598333/findingpheno-multi-omics-data <p>FindingPheno is developing a new computational framework for multi-omic datasets, providing the tools to better understand how host-microbiome interactions can affect growth and other outcomes. We combine state-of-the-art statistical methods with biological knowledge to create our framework, then train and test against data from commercially important crops and animals.</p> <p>The end goal of FindingPheno is to find the true drivers of phenotype in food production systems to unlock the full potential of microbiome interventions for health and sustainability.</p> <p>We are an EU H2020 Research and Innovation Action funded under Horizon 2020, spanning 4 years (2021-2025) and with 8 partners across 5 countries. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952914</p> <p>For further info please see:<br /> Website: https://www.findingpheno.eu/video1</p> <p>Twitter: <a href="https://twitter.com/FindingPhenoEU">https://twitter.com/FindingPhenoEU</a><br /> Blog: <a href="https://www.findingpheno.eu/blog">https://www.findingpheno.eu/blog</a><br /> LinkedIn: <a href="https://www.linkedin.com/company/7685">https://www.linkedin.com/company/7685</a>...</p> <p>Produced in collaboration with MadeClear: <a href="https://www.madeclear.dk/en/">https://www.madeclear.dk/en/</a></p><p><a href="http://video.ku.dk/photo/75598333/findingpheno-multi-omics-data"><img src="http://video.ku.dk/64968568/75598333/e5be181a3ed7cf8e27927a2bffcf03cc/standard/download-7-thumbnail.jpg" width="75" height=""/></a></p> http://video.ku.dk/photo/75598333 Wed, 27 Apr 2022 14:27:21 GMT FindingPheno: Multi-omics data analysis for genotype-phenotype associations.mp4 FindingPheno is developing a new computational framework for multi-omic datasets, providing the tools to better understand how host-microbiome interactions can affect growth and other outcomes. We combine state-of-the-art statistical methods with biological knowledge to create our framework, then train and test against data from commercially important crops and animals. The end goal of FindingPheno is to find the true drivers of phenotype in food production systems to unlock the full potential of microbiome interventions for health and sustainability. We are an EU H2020 Research and Innovation Action funded under Horizon 2020, spanning 4 years (2021-2025) and with 8 partners across 5 countries. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952914 For further info please see: Website: https://www.findingpheno.eu/video1 Twitter: https://twitter.com/FindingPhenoEU Blog: https://www.findingpheno.eu/blog LinkedIn: https://www.linkedin.com/company/7685... Produced in collaboration with MadeClear: https://www.madeclear.dk/en/ FindingPheno is developing a new computational framework for multi-omic datasets, providing the tools to better understand how host-microbiome interactions can affect growth and other outcomes. We combine state-of-the-art statistical methods with... Københavns Universitets Videoportal 02:15 <p>FindingPheno is developing a new computational framework for multi-omic datasets, providing the tools to better understand how host-microbiome interactions can affect growth and other outcomes. We combine state-of-the-art statistical methods with biological knowledge to create our framework, then train and test against data from commercially important crops and animals.</p> <p>The end goal of FindingPheno is to find the true drivers of phenotype in food production systems to unlock the full potential of microbiome interventions for health and sustainability.</p> <p>We are an EU H2020 Research and Innovation Action funded under Horizon 2020, spanning 4 years (2021-2025) and with 8 partners across 5 countries. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952914</p> <p>For further info please see:<br /> Website: https://www.findingpheno.eu/video1</p> <p>Twitter: <a href="https://twitter.com/FindingPhenoEU">https://twitter.com/FindingPhenoEU</a><br /> Blog: <a href="https://www.findingpheno.eu/blog">https://www.findingpheno.eu/blog</a><br /> LinkedIn: <a href="https://www.linkedin.com/company/7685">https://www.linkedin.com/company/7685</a>...</p> <p>Produced in collaboration with MadeClear: <a href="https://www.madeclear.dk/en/">https://www.madeclear.dk/en/</a></p><p><a href="http://video.ku.dk/photo/75598333/findingpheno-multi-omics-data"><img src="http://video.ku.dk/64968568/75598333/e5be181a3ed7cf8e27927a2bffcf03cc/standard/download-7-thumbnail.jpg" width="75" height=""/></a></p> center for evolutionary hologenomics FindingPheno genotype machine learning multidisciplinary Multiomics phenotype http://video.ku.dk/photo/58686546/studiemiljo-diku-2019 <p>Max Kragballe, Kandidatstuderende på Datalogi, fortæller om studiemiljøet på Datalogisk Institut.</p><p><a href="http://video.ku.dk/photo/58686546/studiemiljo-diku-2019"><img src="http://video.ku.dk/49543313/58686546/4584697b1fe4b2ef2dc7587124b3ea1b/standard/download-2-thumbnail.jpg" width="600" height="338"/></a></p> http://video.ku.dk/photo/58686546 Mon, 16 Dec 2019 14:19:53 GMT Studiemiljø DIKU 2019 Max Kragballe, Kandidatstuderende på Datalogi, fortæller om studiemiljøet på Datalogisk Institut. Max Kragballe, Kandidatstuderende på Datalogi, fortæller om studiemiljøet på Datalogisk Institut. Københavns Universitets Videoportal 00:28 <p>Max Kragballe, Kandidatstuderende på Datalogi, fortæller om studiemiljøet på Datalogisk Institut.</p><p><a href="http://video.ku.dk/photo/58686546/studiemiljo-diku-2019"><img src="http://video.ku.dk/49543313/58686546/4584697b1fe4b2ef2dc7587124b3ea1b/standard/download-2-thumbnail.jpg" width="600" height="338"/></a></p> datalogi datalogi-økonomi datalogisk institut datavidenskab diku machine learning studiemiljø http://video.ku.dk/photo/52308836/laes-machine-learning-og <p>Mød studielederen, som fortæller om uddannelsen, samt en kandidatstuderende med fokus på machine learning. Desuden fortæller en data scientist på Lundbeck om sit arbejde med at analysere data fra patienter med Alzheimers.</p><p><a href="http://video.ku.dk/photo/52308836/laes-machine-learning-og"><img src="http://video.ku.dk/49543315/52308836/472d2fb0b5221fc6a7f7a56ff9da2390/standard/download-5-thumbnail.jpg" width="600" height="338"/></a></p> http://video.ku.dk/photo/52308836 Mon, 20 May 2019 14:13:03 GMT Læs machine learning og datavidenskab på Københavns Universitet Mød studielederen, som fortæller om uddannelsen, samt en kandidatstuderende med fokus på machine learning. Desuden fortæller en data scientist på Lundbeck om sit arbejde med at analysere data fra patienter med Alzheimers. Mød studielederen, som fortæller om uddannelsen, samt en kandidatstuderende med fokus på machine learning. Desuden fortæller en data scientist på Lundbeck om sit arbejde med at analysere data fra patienter med Alzheimers. Københavns Universitets Videoportal 03:49 <p>Mød studielederen, som fortæller om uddannelsen, samt en kandidatstuderende med fokus på machine learning. Desuden fortæller en data scientist på Lundbeck om sit arbejde med at analysere data fra patienter med Alzheimers.</p><p><a href="http://video.ku.dk/photo/52308836/laes-machine-learning-og"><img src="http://video.ku.dk/49543315/52308836/472d2fb0b5221fc6a7f7a56ff9da2390/standard/download-5-thumbnail.jpg" width="600" height="338"/></a></p> AI data datalogi data science datavidenskab det natur- og biovidenskabelige fakultet Københavns Universitet kunstig intelligens machine learning matematik science statistik