CMSE Bioinformatics Spring 2019 Modular Courses
CMSE Bioinformatics Spring 2019 Modular CoursesJanuary 9th, 9:00AM to April 25th, 9:00AM
Instructor: Dr. Alexis Black Pyrkosz
These (1 month, 1 credit) graduate level modules are designed for busy graduate students who need to learn computational skills while balancing their work in the research lab. Track 1 provides a practical introduction to basic programming, statistical and data handling concepts. Track 2 focuses on analyzing bioinformatics data including genomic and RNA-seq data.Register Now
- Track 1 meets Mondays and Wednesdays in 129 Hubbard Hall
- Track 2 meets Tuesdays and Thursdays in 128 Hubbard Hall
Email firstname.lastname@example.org for registration overrides for these courses.
Postdocs, faculty, and other MSU-affiliated non-students interested in auditing should complete the audit workshop registration form. For $50 per person per semester, an auditor can access the video lectures and other materials, and can participate in class as their schedule allows. Email your completed form to the Bioinformatics Program Coordinator at email@example.com.
CMSE890:301-Programming Foundations for Bioinformatics
This course is for the absolute beginner to programming. Topics include using R/RStudio, data structures, control structures, external packages, tidying data, and making publishable figures and documents. No prerequisite. January 9 - February 6.
CMSE890:302-Statistical Analysis and Visualization of Biological Data
This course is for biology students who have minimal background in statistics. Topics include summary statistics, probability distributions, confidence intervals, P-values, ANOVA, and regression. Prerequisite: CMSE890:301. February 18 - March 20.
CMSE890:303-Data Handling: Unix and Python
This course is for students who need to handle huge data files. Topics include navigating Unix on the MSU High Performance Compute Cluster, bash scripting, job management, Python scripting, and Jupyter Notebooks. No prerequisite, but coenrollment in CMSE890:301 strongly suggested. January 15 - February 7.
This course is for beginners in genomic data analysis. Topics include sequencing technologies, quality control, read alignment, variant detection, and genome assembly. Prerequisite: CMSE890:303. February 19 - March 21.
This course is for beginners in RNA-Seq. Topics include quality control and alignment, expression quantification, differential gene expression, pathway enrichment, and network analysis. Prerequisite: CMSE890:302/304. April 2 - April 25.