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BIOST 2055 - INTRODUCTORY HIGH-THROUGHPUT GENOMIC DATA ANALYSIS 1: DATA MINING AND APPLICATIONSMinimum Credits: 3 Maximum Credits: 3 This course is a graduate level introduction and overview of modern high-throughput genomic data analysis. It is designed for graduate students in biostatistics and human genetics who are interested in the technology and elementary data mining of high-throughput genomic data (including but not limited to classical expression arrays, various array-based applications, next-generation sequencing and proteomics). The course is also helpful for biology students with basic quantitative training (e.g. two elementary statistics courses and R programming) who have interests in understanding the intuition and logic underlying the data analysis methods. R is the major language used in the course. Academic Career: Graduate Course Component: Lecture Grade Component: Grad Letter Grade Course Requirements: PREQ: BIOST 2039; PLAN: Biostatistics (MS or PHD)
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