BIST-532-01 Machine Learning for Bioinformatics
Fall for 2017-2018
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This course is a combination of theories and empirical skills on managing, processing and analyzing high-throughput biomedical data generated from a variety of "Omics" technologies, which spans genomics, trascriptomics, proteomics, and metabolomics. It introduces the students to the conceptual and experimental background, together with specific guidelines for handling raw data. Hand-on skills with R/Bioconductor and other software tools will be covered on popular "Omics" applications, such as microarray gene expression profiling, mass spectrometry-based metabolomics, RNA-seq, pathway analysis, and etc.
Credits: 3
Prerequisites: BIST 511, BIST 512, BIST 514
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