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    Statistical and Machine Learning Approaches for Investigating Viruses and Virus-Host Interactions

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    Statistical and Machine Learning Approaches for Investigating Viruses and Virus-Host Interactions

    YouTube·Machine Learning

    Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore statistical and machine learning methods for identifying novel viruses and virus-host interactions in this comprehensive conference talk. Delve into the crucial role viruses play in controlling bacterial populations, altering host metabolism, and impacting microbial communities in environments such as the human gut, soil, and oceans. Learn about cutting-edge tools developed for virus research, including DeepVirFinder, DeepMicroClass, VirHostMatcher, VirHostMatcherNet, and ContigNet. Discover computational methods for analyzing metagenmic Hi-C data to improve metagenome assembly and link mobile genetic elements to their hosts. Gain insights into how these advanced tools can be applied to metagenomic data to further explore mobile genetic elements and their interactions with hosts, advancing our understanding of viral ecology and microbial community dynamics.

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