Course Description
Designed for students to learn how modern problems in medicine, agriculture, and biology are solved using big data “omics.” Topics include comparative gene and genome sequence analyses, transcriptomics, metabolomics, phylogenomics, and application of these approaches in medical, agricultural, and environmental sciences. No prior computational experience required.
Additional Requirements for Graduate Students:
Graduate students will be required to write a report on an
assigned topic, and will then present an overview of their report
to the class as a whole.
Athena Title
Bioinformatics and Omics
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
This course is designed for students who wish to learn how computational technologies solve molecular genetic and genomics problems. This course offers a “peek inside the black box” for several commonly used algorithms. Students should learn basic algorithms and programming concepts that underlie the fast-paced fields of genomics and bioinformatics. Upon completion of the course, students will be able to understand what current research in bioinformatics is trying to accomplish and will be able to read with comprehension some of the research literature of the area. No prior computing experience is expected.
Topical Outline
• Molecular Biology • Information Organization and Sequence Databases • Molecular Evolution • Substitution Matrices • Pairwise Sequence Alignment • BLAST and Multiple Sequence Alignment • Protein Structure Prediction • Phylogenetics • Genome Assembly and Annotation • Environmental Genomics • Transcript and Protein Expression Analysis • Metabolomics • Basic Probability • Advanced Probability for Bioinformatics Applications • Programming Basics and Applications to Bioinformatics • Developing a Bioinformatics Tool
Syllabus