CMSE 890 (006) and CMSE 491 (001) - Computational Medicine (Fall 2018)
Description: This course provides a survey of, and experience in, applying quantitative and computational techniques in contemporary biomedical research, based on diverse large-scale data. Three major components include: 1) Lectures to introduce biomedical questions, critical datasets, and statistical/machine learning techniques. 2) Real- world case-studies guided by discussions of recent seminal papers of data-driven biomedical research. 3) Group projects to utilize computational methodology to answer open biomedical questions.
Time: Mon/Wed/Fri 9:10-10:00 a.m. in 217 Berkey Hall
Prerequisites: CMSE 201 or equivalent and two semesters of introductory biology. Statistics at the level of STT 231 is strongly recommended. This course is open to both undergraduate and graduate students!
Instructor: Prof. Jianrong Wang in CMSE.
Major topics covered:
- Exploratory data analysis and visualization.
- Large datasets and basic database usage
- Genetic variation and GWAS
- Functional genomics and annotation
- Transcriptomics and gene modules,
- Epigenomics, gene regulation and high-dimensional data
- Networks on gene expression
- Molecular phenotypes, eQTLs and biological pathways
- Systems genetics and fine-mapping
- Cancer genomics
- Single-cell data analysis
- Precise genome editing
- Drug discovery
- Personalized medicine
- Statistical data analysis, hypothesis testing and analysis of variance
- Machine learning, statistical learning and classification
- Data integration