Selected Topics in Zoology (Section 34684):
Introduction to Computational Data Processing in Biology
BIOL L507 (Z620) Spring 2014
Time & Location: Mon, Wed 1:00p - 2:15p (Credits: 1.5); Lindley Hall (LH) 030
Instructors: Volker Brendel (205C Simon Hall; Tel.: 855-7074)
Mon, Wed after class and by appointment.
Grades: will be determined as described below.
You will have access to networked computer terminals in class and will need such basic access outside of the classroom for assignments.
HTML version of this syllabus
SynopsisComputational approaches have become an integral part of research in all areas of biology, pervading data retrieval, management, mining, and analysis. Researchers rely on an array of tools and skill sets, including web services and workflow management systems. Appropriate foundational skills include proficiency with some scripting language and some statistical analysis software. This course seeks to impart such proficiency with the Perl scripting language, the widely-used BioPerl modules, and the R statistical package. Applications will be drawn largely from genomics, but tailored to participating students’ needs.
PrerequisitesThis class is directed primarily at first- and second-year graduate students in the Biology Ph.D. program. Participants are expected to have passed the introductory BIOL Z620 Bioinformatics2Go course; similar background experience can serve as a substitute with permission of the instructors.
Classes will be taught in a computer lab. Students are required to be familiar with basic computer operational skills, although no programming language knowledge will be assumed. Class messages and materials, including assignments, will be shared through our Oncourse site in addition to these web pages, and students are required to regularly check these relevant communication channels.
IU is committed to Creating a Positive Environment for teaching and learning. If you have any concerns or suggestions, please let the instructor know.
AssignmentsMost class periods will begin with a brief introduction to a particular topic, followed byindividual work on associated in-class assignment. In addition to the in-class work, there will be homework assignments. Students are expected to prepare for class by completing posted assignments in timely fashion. It is anticipated that completion of the assignments will require about 3 hours of work outside the classroom per week.
GradingGrades will be based on successful completion of the homework assignments (20%), two in-class tests (20% each), and an individual final project (40%).
Final projects will consist of short, manuscript-style reports on individual data analysis projects covering multiple themes of the class. The main teaching goal with the final projects is for students to learn best practices for design and documentation of typical computational approaches in biology.
Text booksThe course does not rely on a textbook. However, we suggest the following background material for those students wishing to consult additional sources:
Learning Perl by Schwartz, Phoenix & Foy
Understanding Bioinformatics by Zvelebil & Baum.
Web-accessible resources will be posted on the appropriate schedule pages.
Selected journalsStudents are encouraged to review current research literature that provides many examples of application of the class topics. The following list provides a selection of relevant journals that are electronically accessible.