ELEC 409 Bioinformatic Analytics Units: 3.00
The course surveys: microarray data analysis methods; pattern discovery, clustering and classification methods; applications to prediction of clinical outcome and treatment response; coding region detection and protein family prediction. At the end of this course, students should be able to appreciate some approaches related to individualizing medical treatment, as well as to apply some of the methods, such as alternatives to PCA, to more traditional engineering problems.
(Lec: 3, Lab: 0, Tut: 0)
(Lec: 3, Lab: 0, Tut: 0)
Requirements: Prerequisites: APSC 174, ELEC 224 or MREN 223, ELEC 326 or ENPH 252
Corequisites:
Exclusions:
Offering Term: F
CEAB Units:
Mathematics 9
Natural Sciences 0
Complementary Studies 0
Engineering Science 18
Engineering Design 9
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Understand pertinent bioinformatics terms (DNA, Genes, Amino Acids, proteins etc.).
- Understand how to find datasets for bioinformatics research.
- Understand the challenges and open issues in bioinformatics.
- Understand techniques for preparation of datasets for processing.
- Understand how to build a clustering or classification algorithm for the dataset.