EE 381V Genomic Signal Processing and Data Science

Spring 2022

Lectures

MW 1:30-3pm, on Zoom until Jan. 31

Textbook

The course has no required textbook. Lecture slides, tutorials, and research papers will be posted to Canvas. Suggested reference: P. Compeau and P. A. Pevzner, Bioinformatics Algorithms, Active Learning Publishers, 2015.

Grading

Tentative grading breakdown.

• Homeworks: 30%
• Midterm exam: 30%
• Final project: 40% (project info page)

Homework policy

Homeworks are to be submitted at the beginning of the class when they are due. You may discuss homework problems with other students, but must submit your own independent solution. Late homework assignments will not be accepted.

Course description

The tremendous advancements in high-throughput DNA sequencing have revolutionized research in biology and are paving the road towards personalized medicine. This course is focused on signal processing and data science problems encountered in analysis of high-throughput genomic data. Topics include DNA sequencing and sequence alignment; genome assembly; genotyping and haplotyping; RNA sequencing; genome compression; biomolecular detection systems including DNA microarrays and quantitative polymerase chain reaction systems; clustering and classification of gene expression data; and modeling and inference for genetic regulatory networks. The problems are approached using methods from machine learning, signal processing, information and communication theory, and combinatorial algorithms. The students will also learn to use software tools for the analysis of sequencing data.

Lecture notes and supporting materials

• Lecture #1: Course goals and overview. Examples of computational problems.

  Supporting material

  • R. Karp, “Mathematical Challenges from Genomics and Molecular Biology,” Notices of AMS, 49(5), pp. 544-553, May 2002.
  • M. C. Schatz and B. Langmead, “The DNA Data Deluge,” IEEE Spectrum, vol. 50, no. 7, pp. 29-33, July 2013.
  • M. W. Libbrecht and W. S. Noble, “Machine learning applications in genetics and genomics,” Nature Reviews Genetics, vol. 16, pp. 321-332, 2015.

• Lecture #2: Molecular biology primer. DNA sequencing.

  Supporting material

  • L. Hunter, “Molecular Biology for Computer Scientists.” An overview of molecular biology concepts. The material most relevant to Lecture #2 is in Section 4.3 and Section 5.
  • Ben Langmead's lecture notes and videos cover several topics that we cover in class.

Notice for students with disabilities

Students with disabilities may request appropriate academic accommodations from the Division of Diversity and Community Engagement, Services for Students with Disabilities, 512-471-6259, http://www.utexas.edu/diversity/ddce/ssd/.

Emergency instructions

All occupants of university buildings are required to evacuate a building when a fire alarm and/or an official announcement is made indicating a potentially dangerous situation within the building. Familiarize yourself with all exit doors of each classroom and building you may occupy. Remember that the nearest exit door may not be the one you used when entering the building. If you require assistance in evacuation, inform your instructor in writing during the first week of class.

For evacuation in your classroom or building:

1. Follow the instructions of faculty and teaching staff.
2. Exit in an orderly fashion and assemble outside.
3. Do not re-enter a building unless given instructions by emergency personnel.