Genomics at Agnes Scott College
I implemented GEP projects into my BIO 260: Bioinformatics course. The course is an introduction to the theory and practice of bioinformatics and computational biology. Topics include: the analysis of genomic sequences, comparative genomics, gene expression arrays and analysis of protein structure. Laboratory includes original research of new genomes, including sequence annotation (GEP project). The course is offered every other year in Spring. Prerequisites include introductory biology sequence and statistics or calculus. Students have included sophomores, juniors and seniors.
I implemented GEP projects into BIO 260 during Spring 2013. To do so, I added a 3-hour lab to my Bioinformatics course, which used to meet for only 3 hours a week as a lecture-only course. In 2013, the class met two times a week, for a total of 6 hours of contact time.
Prior to implementing GEP in BIO 260, I pilot-tested GEP work with three students enrolled in independent research project course during Spring and Fall 2012. One of my students was trained as a TA at GEP TA training workshop in January 2012.
Lessons Learned and Future Plans
I originally hoped to implement both annotation and sequence improvement aspects of the project. However, the lack of dedicated computer lab, where sequence improvement software could be installed, made the finishing aspect of the project difficult to execute. Because of that limitation experienced during my pilot testing stage with independent research students, I decided to focus on annotation only.
Students worked in groups of two on annotation projects. This format allowed the more experienced students (who did annotation as a part of a special project the semester before taking BIO 260) a chance to mentor the students new to annotation. I plan to keep the teamwork format next time I teach the course.
I noticed that the 2 x 3 hour format did not work well in terms of scheduling. My college only offers three-hour blocks in the afternoons (2-5p), and those are usually used for labs. Scheduling my class for two afternoons a week created conflicts with other science courses students need to take. Next time I offer the course, I plan to use the format 2*75minute morning class+ one 3-hour afternoon lab. Feedback I received during the alumni workshop suggests that this format seems to work well for others.
In addition to formal and informal presentations during the semester, two of my students also presented their annotation work to the college-wide community during SpARC (Spring Annual Research Conference) in April 2013. Next time I teach the course, I plan to encourage all of the students to present either a poster or an oral presentation at SpARC. This presentation gave the students a valuable opportunity to reflect on broader aspects of the project, and to think of how to explain the relevance of their work to a broad audience.
Syllabus for BIO 260: Bioinformatics
Biology 260: Bioinformatics
Class times: Thursday 2-5 pm, BSC 111W
Professor: Srebrenka Robic
Office: Bullock Science Center 203W
Office hours: Mondays 1-2 pm.., Wednesdays 12-1 pm, and other times by appointment.
Textbook: Genomics, Proteomics, & Bioinformatics by Campbell and Heyer
Textbook website: http://wps.aw.com/bc_campbell_genomics_2/
Course website on Moodle: IMPORTANT: The details of this syllabus might change. This syllabus will be updated on Moodle site. Also, assignments, some lecture notes, and additional handouts will be posted on Moodle. It is your responsibility to check the website and your college email regularly.
Focus of the course: One of the main reasons why biological sciences today are vastly different from biology 10-15 years ago is the amazing abundance of genome-wide information about DNA and protein sequences. Bioinformatics is a new field which aims to analyze those data and use them to explain biological phenomena.
This is a hands-on course in Bioinformatics that will emphasize how to use computers and the web as tools to analyze and represent large collections of biological sequence and structure data. Lecture, discussion and computer activities will be integrated during each class period. Because of such integrative, hands-on nature of this course, attendance is absolutely essential. You will also be expected to do computer-based work and research outside of the class period.
Course goals: The goal of this course is to help you develop basic competencies on finding, accessing and analyzing biological sequence and structure data. At the end of this course you will be familiar with sequence and structure databases, and will know how to extract and analyze information from those databases. You will also learn how to apply bioinformatics tools to relevant questions in molecular biology, genetics and evolution by carrying out an independent, question-driven computational project.
Homework/Computer Laboratory/Discussion 200 pts
Two midterm Exams 100 pts
Final Project and Presentation 100 pts
TOTAL: 400 pts
A = 92.0-100%, A- = 90.0-91.9%, B+ = 88.0-89.9%, B = 82.0-87.9%, B- = 80.0-81.9%, C+ = 78.0-79.9%, C = 72.0-77.9%, C-70.0%-71.9%, D+ = 68.0-69.9%, D = 62.0-67.9%, D- = 60.0-61.9%, F = below 60%
The main difference between this and other biology courses is that both in class and at home you will be expected to carry out computer-based activities and investigations. While there is no formally scheduled lab period for this class, you will be expected to spend some computer lab time outside of the regularly scheduled class period every week. You will be asked to turn in your work (homework and in-class work) on a weekly basis, and this will constitute a large portion of your grade for this class.
You should get a three-ring binder for this class and keep a neatly-organized record of your activities in it. Each time you work on homework assignments and/or projects outside of the regular class period, record the date and time on computer, and record what you did, what problems you might have run into etc. I encourage you to work with each other and collaborate on all homework assignments. Real science is never done in isolation, and you will learn more by working in groups. Each person still needs to turn in their own assignments, written in their own words. Please give credit, in writing, to the person(s) you worked with if your work was done collaboratively.
One quarter of your grade will be based on your final project and presentation. You will research an unanswered question in biology (molecular biology, genetics, evolution or protein science) using bioinformatics tools. Your project will contain a Powerpoint presentation, a research report, supporting data set and a website on your e-portfolio. I will provide more information about this later in the semester. A successful project may lead to a SpARC presentation in this or next year’s SpARC. I would like to encourage each one of you to seriously consider this possibility.
Near the end of the semester you will be notified by e- mail and provided with a link to follow to complete the evaluations online outside of class. Your feedback on the course is extremely valuable to me, the department, and the administration. I will take your comments very seriously and use them to improve the course the next time we teach it. You are responsible for completing an evaluation for each of the two instructors of the course at the end of the semester. I will provide more details later.
Date Topic Pages to read
01/20 Introduction to the course and Bioinformatics 2-31
Coin Toss Probability with Excel
01/27 Access and analysis of genomic sequences 33-83
Consult about genome presentation
Nucleotide toss probability with Excell
02/03 Making sense of large genomes 83-109
Present a newly sequenced genome
Data-mining in-class activity
02/10 Comparative genomics and evolution 114-139
Reading phylogenetic trees
02/17 Forensic and biomedical bioinformatics 145-175
Discussion of ethical issues
Student presentations about new drugs
02/24 Why can’t I just take a pill to lose weight? 219- 232
“Metabolomics” and interaction networks
Modeling with Excel and Cell Designer
03/03 Exam #1
Discussion of preliminary project proposals
03/10 Intro to microarrays 233-245
Learning about evolution from molecular data 139-145
Continue modeling with Excel and Cell Designer
03/24 Visualizing protein 3D structures 285-298
Structure-based drug design
03/31 Protein detection tools 307-328
Computing structural parameters
Discussion of a proteomics research paper
04/07 Why can’t we cure more diseases? 330-340
Synthetic biology 394-407
04/14 Systems biology: putting it all together 409-418
All the “omics” of biology –what next?
04/21 Final student presentations
Research reports due.
04/28 No class – SpARC
Exam #2 due (take-home)