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!

Textbook:  None

Instructor:  Prof. Jianrong Wang in CMSE.

Major topics covered:

  1. Exploratory data analysis and visualization.
  2. Large datasets and basic database usage
  3. Genetic variation and GWAS
  4. Functional genomics and annotation
  5. Transcriptomics and gene modules,
  6. Epigenomics, gene regulation and high-dimensional data
  7. Networks on gene expression
  8. Molecular phenotypes, eQTLs and biological pathways
  9. Systems genetics and fine-mapping
  10. Cancer genomics
  11. Single-cell data analysis
  12. Precise genome editing
  13. Drug discovery
  14. Personalized medicine
  15. Statistical data analysis, hypothesis testing and analysis of variance
  16. Machine learning, statistical learning and classification
  17. Data integration