Computer Science & Engineering
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Instructor

Brian Chen (Spring 2016)

Current Catalog Description

Computational problems and their associated algorithms arising from the creation, analysis, and management of bioinformatics data. Genetic sequence comparison and alignment, physical mapping, genome sequencing and assembly, clustering of DNA microarray results in gene expression studies, computation of genomic rearrangements and evolutionary trees. Credit will not be given for both CSE 308 and CSE 408. No prior background in biology is assumed. Prerequisite: CSE 17 or 18 or permission of the instructor.

References:

Neil C. Jones and Pavel A. Pevzner, "An Introduction to Bioinformatics Algorithms", 1st Edition,  MIT Press, 2004 ISBN 978-0262101066

Jonathan Pevsner, "Bioinformatics and Functional Genomics", 2nd Edition, Wiley-Blackwell, 2009, ISBN 978-0470085851

COURSE OUTCOMES

Students will have:

  1. Ability to write computer programs in Perl to analyze bioinformatics data.
  2. Ability to choose appropriate algorithms and data structures when programming solutions to bioinformatics problems.
  3. Ability to communicate technical material relating to bioinformatics algorithms and applications.
  4. Ability to recognize moral and ethical issues arising from creation of software for bioinformatics applications.

RELATIONSHIP BETWEEN COURSE OUTCOMES AND STUDENT ENABLED CHARACTERISTICS

CSE 308 substantially supports the following student enables characteristics

A. An ability to apply knowledge of computing and mathematics appropriate to the discipline

B. An ability to analyze a problem and identify and define the computing requirements appropriate to its solution

I. An ability to use current techniques, skills, and tools necessary for computing practices

J. An ability to apply mathematical foundations, algorithmic principles, and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices

K. An ability to apply design and development principles in the construction of software systems of varying complexity

 

Major Topics Covered in the Course

  1. The Pervasive Nature of Computation in Science
  2. Introduction to Molecular Biology
  3. How Molecular Biology Translates to Computer Science
  4. Introduction to UNIX
  5. Editing, Automation, and Remote Access
  6. Pyrosequencing
  7. Genome sequencing Assembly
  8. Hands on with SSAKE
  9. Sequence Assembly Algorithms
  10. Hashing in Sequence Assembly
  11. Solexa Sequencing
  12. Exploiting Paired End Reads
  13. Path Compression in Genome Assembly
  14. Biomedical Applications of DNA Arrays
  15. Genome Annotation
  16. Finding Genes with Genemark and Glimmer
  17. Nucleotide Sequence Alignment Part I
  18. Markov Models for Genome Annotation
  19. Nucleotide Sequence Alignment Part II
  20. Dynamic Programming with Affine Gap Penalties
  21. Backtracking on Affine Gap Tables
  22. Applications of Sequence Alignment and Gene Prediction
  23. Genome Evolution
  24. Phylip and Phylogenies
  25. Building Phylogenetic Trees I
  26. Building Phylogenetic Trees II
  27. Phylogeny and Molecular Biology
  28. Finding Active Sites Through Phylogenetic Analysis

Assessment Plan for the Course

The students are given five substantial homework assignments, some of which include programming problems. Written homework questions account for 20% of their course grade and programming problems account for another 20%. They also maintain a "lab notebook" which records their observations when performing Web Exploration projects assigned from their Exploring Bioinformatics textbook. This accounts for 10% of their course grade. Students are also required to write a final 15-page research paper on a bioinformatics topic relating to the course, and to give a 15-minute talk on this work during the final week of the course. This final paper/project accounts for 50% of their course grade.

How Data in the Course are Used to Assess Program Outcomes (unless adequately covered already in the assessment discussion under Criterion 4)

Each semester I include the above data from the assessment plan for the course in my self-assessment of the course. This report is reviewed, in turn, by the Curriculum Committee.