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Videos

 
Not What but Why: Machine Learning for Understanding Genomics
Video

Machine learning and artificial intelligence are changing the nature of biological research, especially genomics. Artificial intelligence applications are opening up our understanding of ourselves and disease, and we must strive to create tools that can work as partners in research, not simply as black boxes. Barbara Engelhardt is an assistant professor in the Computer Science Department at Princeton University since 2014. She graduated from Stanford University and received her Ph.D. from the University of California, Berkeley, advised by Professor Michael Jordan. She did postdoctoral research at the University of Chicago, working with Professor Matthew Stephens, and three years at Duke University as an assistant professor. Interspersed among her academic experiences, she spent two years working at the Jet Propulsion Laboratory, a summer at Google Research, and a year at 23andMe, a DNA ancestry service. Professor Engelhardt received an NSF Graduate Research Fellowship, the Google Anita Borg Memorial Scholarship, the Walter M. Fitch Prize from the Society for Molecular Biology and Evolution, an NIH NHGRI K99/R00 Pathway to Independence Award, and the Sloan Faculty Fellowship. Professor Engelhardt is currently a PI on the Genotype-Tissue Expression (GTEx) Consortium. Her research interests involve statistical models and methods for analysis of high-dimensional data, with a goal of understanding the underlying biological mechanisms of complex phenotypes and human diseases. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

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Metabolomics: You Are What You Eat
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NASA’s Human Research Program releases “Metabolomics: You Are What You Eat” video to highlight its Twins Study which uses omics to study Mark and Scott Kelly’s metabolites. Omics is an evolving field integrating collections of measurements, biomolecules and sub-disciplines to provide a more complete picture of health.

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A Voice for Diversity in Science
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Only 17% of the English-language biographies on Wikipedia are about women – but the statistic won’t stay that low for long if Dr Jess Wade has her way. A passionate advocate for diversity in science, Jess balances her work as an award-winning physicist at Imperial College London with her role as a ‘Wikipedian’, creating and uploading the biographies of underrepresented groups in science.

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Cancer: Who Lives? Who Dies?
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Ted Goldstein is a Silicon Valley tech executive turned cancer researcher. After a successful career and an instrumental role as top executive at Apple, Ted returned to College to obtained his Ph.D. in Bioinformatics and Biomolecular Engineering to study cancer and to approach the disease the way software engineers approach difficult problems.

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Seattle Children's Hospital SIDS Research with Microsoft Genomics
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Discover how Microsoft Genomics is empowering organizations to explore new avenues of research. The Seattle Children's Hospital SIDS (Sudden Infant Death Syndrome) research with Microsoft Genomics uses Microsoft AI to analyze data in a massive scale. With Microsoft AI, Seattle Children's Hospital is able to identify genetic contributions to pediatric disorders and come closer to reaching their goals of recognizing SIDS earlier and preventing it from happening.

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How To Select a LIMS
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With so many LIMS to choose from, how can you be sure you’re choosing the right LIMS for your lab? In this short video, learn the steps to make the best, most informed decision when it comes to selecting a new LIMS.

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How Much Does a LIMS Cost?
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The actual costs of LIMS solutions vary greatly. In this video from CSols Inc, the different sources of cost in implementing a LIMS are explored including licensing, hardware and data migration.

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Remodelling Machine Learning: An AI That Thinks like a Scientist
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Modern machine learning is great for helping scientists sort through huge data sets. But it’s less useful for things that require inference or reasoning – both vital to the scientific process. One group of scientists are now trying to fix this problem with a new kind of machine learning. This new approach aims to find the underlying algorithmic models that interact and generate data, to help scientists uncover the dynamics of cause and effect.

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Top 5 LIMS and LIMS Consulting Myths - Busted
Video

Having been in the Laboratory Informatics and LIMS Consulting business for quite some time, we at CSols, Inc. have been exposed to many myths and misconceptions. While there may be a small kernel of truth to some of these, for the most part these statements do not hold water. In this video, we listed out the top five myths and “Bust” them.

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Top Science Stories of 2018
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We have seen some amazing scientific breakthroughs in 2018. Here is a selection of our favorites.

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