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)
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 (papers):
- 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, July 2013, pp: 29-33.
- M. W. Libbrecht and W. S. Noble,
"Machine learning applications in genetics and genomics,"
Nature Reviews Genetics, vol. 16, 2015, pp. 321-332.
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, 471-6259, http://www.utexas.edu/diversity/ddce/ssd/.
Emergency instructions: Classroom evacuation for students
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For evacuation in your classroom or building:
- Follow the instructions of faculty and teaching staff.
- Exit in an orderly fashion and assemble outside.
- Do not re-enter a building unless given instructions by emergency personnel.
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