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Computational Genomics

Course summary: The science of genomics involves the intersection of experimentation and computation. Computers are quite obviously required to handle the massive amount of data produced by genome sequencing projects. More importantly however, genome sequencing efforts yield ‘information’ alone, which can only be converted into ‘knowledge’ through the use of computers. In this class, the students will convert raw genomic information (i.e. sequence reads) into knowledge through the use of computational genomics tools and applications. The class will be provided with unassembled genome sequence data from the Centers for Disease Control and Prevention (CDC) and will proceed through five distinct stages of analysis and interpretation of that data:

  • 1 - genome assembly
  • 2 - gene prediction
  • 3 - functional annotation
  • 4 - comparative genomics
  • 5 - production of a predictive webserver

This course will be entirely practical in nature. Students will learn to do the actual work of computational genomics. Expert guest lecturers will be brought in to provide information on state-of-the-art computational genomics tools. Based on this information, other class lectures and their own research, students will be solely responsible for choosing which tools (e.g. programs and/or databases) to use, how to implement them and for producing and thoroughly documenting their final results. All results will be integrated into a publicly available genome browser.

This class meets on Tuesdays and Thursdays from 1:30 to 2:45 pm in Klaus Advanced Computing Building 1447. Students will also have access to a dedicated Linux server for hosting purposes. There is no textbook. Required and recommended readings will be made available on the course Wiki page - along with any lecture material. Students are required to use online databases and the scientific literature to inform their choice of computational tools to be used. Since there is no textbook and many of the sessions involve class discussion and lab activities rather than formal lecture, attendance and class participation are mandatory.


  • Class participation 12.5%
  • Group presentation I 12.5%
  • Group presentation II & Lab 12.5%
  • Group presentation III & Demo 12.5%
  • Final Results & Documentation 50%

Class attendance and participation are mandatory. Class participation will be judged by the degree to which each student participates in class lectures and discussions (by asking questions, answering questions, offering ideas and opinions), during group presentations (by asking questions during others’ presentations, by engaging the audience during their own presentation, by connecting their presentation to previous class discussions, by working successfully in a small group), and during computer laboratory activities (by performing analyses and working with other students). Students who show up late or miss class will be severely penalized.

Each group will give a series presentations and laboratories/demos. Group presentations and labs/demos will be judged by the depth of analysis presented, the clarity of presentation, the utility of the exercises, the appropriateness and justification of the choices made, the validity and robustness of the results and the thoroughness of the documentation. In addition to presentations, results and documentation should be presented on the class Wiki site. Specific requirements for the presentations will be provided during class sessions.

Please see for Georgia Tech’s Academic Honor Code, which you are required to uphold.

Professor: I. King Jordan king.jordan AT EBB 2109 404-385-2224
T.A.: Aroon Chande arch AT EBB 2200
Office hours are available on request.

Course Materials

Guest Lecturers

Working Groups

Team I:

Team II: