Current Topic. This course establishes a foundation in applied statistics and data science in biology for those interested in pursuing data-driven research. Students will develop fundamental and transferable computational and statistical skills for critically thinking about and using data in biology. The course will develop the foundations of and illustrate major methods applied in modern biological problems and data sets. Data science topics will include data wrangling, exploration and visualization, data resampling, clustering, dimensionality reduction, manifold learning, random forests, kernel methods, and latent space models. The course will explore application of these methods in the context of gene regulatory networks, genotype to phenotype mapping, chromatin structure analysis, single-cell biology, and quantitative biological imaging. The python programming language is extensively used to explore methods and analyze data.

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