Course title:
Special topic course STAT 892 - 004 - Integrative Data Science for Plant Phenomics
Available to:
Statistics and Non-Statistics Graduate Students
Course Description:
This is a course on data science in the context of plant phenomics. The main data types will include genomic data, image-based phenomic data, metabolomic data, and transcriptomic data and among others. Students will become proficient in the principles, statistical models and practice of data-driven genome-to-phenome analysis via multi-type data integration; and hands-on experience in data analysis using R and/or Matlab. Successful completion of this course will enable students to process and integrate these data types and build genomic linkages. The students' performance will be assessed based on participation/homework and a course project on data analysis in plant phenomics.
Time and Room: Tu and Th 11AM-12:15PM at KEIM-262EAST
Instructors:
Gota Morota (Animal Science), Toshihiro Obata (Biochemistry) and Qi Zhang (Statistics).
Guest lectures:
Harkamal Walia (Agronomy), Hongfeng Yu (CSE) and Chi Zhang (SBS).
Students interested in this course should enroll through MyRed for 3 credits. Any questions can be directed to any of the listed instructors.