Shan Hays and Andrew Keck, Western State College of Colorado
Genome Analysis at Western State Colorado University (Shan Hays)
We (Shan Hays and Andy Keck) cotaught this course to a class composed of two distinct sets of students: biology majors who had at least taken genetics and computer science/math students who had at least taken an introductory course on computer programming. We paired one member from each group together and had them carry out various tasks involving genomic data, most of which involved programming with R. We also incorporated one month of annotation of the D. biarmipes genome
We spent much of this semester developing the course as we delivered it. This allowed us to spend more time concentrating on interesting questions as students discovered them while they analyzed genomic sequences. We were also better able to gauge the students' ability to delve further into different aspects of genomic analysis. Consequently, we delivered a course at a level appropriate for the students in the course.
Since we had students with very different backgrounds, the biology students could help teach the computer scientists/mathematicians about the underlying biology, while the computer scientists/mathematician helped the biology students understand the programming and the computational algorithms used in the genomic analysis.
Lessons Learned and Future Plans
A major impetus for offering this course was to introduce biologists to the computational analyses that are becoming commonplace in molecular biology and to give the computer scientists and mathematicians real problems to solve with their programming and mathematical skills. Unfortunately, these two groups of students seem to exist in silos at the University and are not given much chance to interact academically, despite the fact that they will be required to do so to succeed professionally. Overall, we believe that we were mostly successful. The students appeared to be very pleased with the course and we enjoyed teaching it and helping the students to understand the role each has to play in solving the problems associated with extensive genomic datasets.
The course we taught was a one-off special topics course, but we would like to see it taught again at a more convenient time and even incorporated into the curriculum. However, achieving this goal will be made difficult by various administrative, financial, and academic challenges. We remain hopeful that we can pull it off.
Syllabus for BIOL 397: Genome Analysis
BIOL/MATH 397: GENOME ANALYSIS
INSTRUCTORS: Dr. Shan M. Hays, Natural and Environmental Sciences
238C Hurst, 943-2552, email@example.com
Office hours: 5-6 MW, 2-3:30 T, 2-3 F, and by appointment
Dr. Andy Keck, Math and Computer Information Science
H212, 943-2802, firstname.lastname@example.org
Office hours: 1-2 MWF, 9-10 M, 9:30-10:30 R, and by appointment
LECTURE/LAB TIMES: 6-8:20 pm Mondays and Wednesdays in Hurst 103
COURSE DESCRIPTION: This course introduces students to the algorithms and techniques used in genome analysis. Students develop software to search for patterns and use standard genome query tools to annotate a segment of fruit fly DNA. Prerequisite: BIOL 312 or MATH 151 or CIS 190.
WORKLOAD: Expect to devote a fair amount of time outside of class (at least four hours per week) to work on projects, papers, posters and presentations. We expect everyone to be prepared for each class so that questions and discussions can be serious and knowledgeable.
COURSE STRUCTURE: This course will be organized around projects. The purpose of this course is to introduce students to research techniques currently in use to analyze large sets of data. Genome analysis involves skills from biology, mathematics, and computer science. Few people have all the skills necessary so collaboration among students will be required. This combination of expertise is becoming more common in academia and biologically-oriented businesses, so we want the students to get used to working with each other now, in anticipation of such collaborations being the norm in your professional lives.
ASSESSMENT: Your grade in this course will be based on your work carried out in group projects. Groups will present their results in written form, in poster form during the spring Celebration of Scholarship, and in oral presentations. Plus/minus grades will be used, where appropriate or earned. For each calendar day an assignment is past due, one letter grade will be deducted.
Class Etiquette: As this course is intended to develop your ability to think logically and critically, active discussion will be encouraged. Please, do not hesitate to ASK QUESTIONS during class! Please come to class on time and remain for the entire session. If you must arrive late or leave early, please sit close to the door to minimize the disruption. If you have electronic communication devices, TURN THEM OFF. Do not plan on being able to be “on-call” when in class due to this.
Class Attendance: Attendance is not optional. Work carried out in-class on assigned projects is the meat of the course. If you are absent, you will be assessed a zero for the work done that day. There are no exceptions and no make-ups. You have been warned.
Disruptive Classroom Behavior: The classroom is a special environment in which students and faculty come together to promote learning and growth. It is essential to this learning environment that respect for the rights of others seeking to learn, respect for the professionalism of the instructor, and the general goals of academic freedom are maintained. Differences of viewpoint or concerns should be expressed in terms which are supportive of the learning process. Student conduct which disrupts the learning process shall not be tolerated and may lead to disciplinary action and/or removal from class.
Extra Credit: Extra credit is NOT available in this course.
Students with Disabilities: Upon identifying themselves to the instructor and the university, students with disabilities will receive reasonable accommodation for learning and evaluation. For more information, contact Academic Resource Center in room 302, Taylor Hall (943-7056).
Cheating and Plagiarism: Cheating is the actual or attempted practice of fraudulent or deceptive acts for the purpose of improving one's grade or obtaining course credit or assisting another student in doing so. Plagiarism is a specific form of cheating which consists of the misuse of the published and/or unpublished works of others by misrepresenting the material (i.e., their intellectual property) so used as one's own work. I will not tolerate cheating or plagiarism! Penalties range from a 0 or F on a particular assignment, through an F for the course, at my discretion. For more information on the College’s policy regarding cheating and plagiarism, refer to pages 34 and 35 of the 2012-13 Catalog.
Registration: The last day to drop the class via WOL is January 29. The last day to withdraw from the class is March 26. Withdrawal requires my signature along with your advisor’s and will result in a W on your transcript and no refund.
SCHEDULE OF TOPICS
We will cover the following topics in roughly this order: Central Dogma, R primer, GC content analysis, dimer analysis, genomics, gene structure, DNA sequence analysis, protein structure, amino acid sequence analysis, proteomics, DNA sequencing and finishing, C-value paradox, repetitive DNA analysis, chromatin, evolution, protein motif analysis, multiple sequence alignments, RNAseq, SNPs, genomic analysis, sequence annotation, microarrays, and analysis of expression data.