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CREATED:20211011
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SUMMARY:Machine Learning for Biologists
DESCRIPTION:The aim of the course is to provide a practical introduction to the analysis of “omics” data. Topics will range from data visualization/exploration to univariate/multivariate analysis and machine learning. Practical examples and applications will be illustrated by using R and Python.\nCourse Milestones:\n\nData exploration and visualization\nUnivariate/Multivariate analysis\nIntroduction to machine learning: classifiers, performance measures, diagnostics\nMachine learning tools for the analysis of Gene Expression data\nThe Data Analysis Plan (DAP) – intro to unbiased pipelines for (binary) classification\nPerformance measures and diagnostic plots – Accuracy, MCC, Stability: theory and graphics\nDifferential network analysis – co-expression networks, graph comparison, community detection: theory and examples in R/Python, visualization by the igraph library and use of the ReNette web interface\nBasic application of ML to gene prediction\n\n
URL:https://www.igb.cnr.it/index.php/events/ngs-for-evolutionary-biologists-from-basic-scripting-to-variant-calling-2-843-909/
CATEGORIES:elixir
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