Digital Biology: A survey of topics in bioinformatics and functional genomics
BIOL-L/MLS-M 388 Spring 2022
Time & Location: Tues, Thur 11:30a - 12:45p (Credits: 3.0); Biology Building (JH) A106
Instructors Volker Brendel (205C Simon Hall)
Email:
VB, vbrendel@indiana.edu
WWW:
https://brendelgroup.org/
Office Hours:
Tues, Thur after class and by appointment.
Grades: will be determined as described below.
Schedule:
https://brendelgroup.org/teaching/2022/DBS22schedule.php
Synopsis
Biology has become one of the primary application domains of computer science and informatics approaches. The term "Bioinformatics" covers a wide spectrum of data management and processing associated with large-scale, high-throughput biological data generation. A significant part of biological research these days is conducted "digitally". This class will survey topics concerning the generation and analysis of biomolecular sequence data (DNA and protein) that underpin much of modern biology, including for example genetics; ecology, evolution, and population biology; and structural biology. Applications in medicine and biotechnology are changing the world we live in. The course should be of interest to you if one or more of the following apply to you: (1) You are curious and would like to learn about a "hot topic"; (2) You want to expand your range of options for graduate school; (3) You are considering a high-paying job in the biotechnology sector.
Prerequisites
This class is directed primarily at upper level undergraduates in Biology, although students of Mathematics, Statistics, Informatics, Data and Computer Science may find the course accessible and of interest. Prerequisite is BIOL 211 or an equivalent course or permission of the instructor. Class messages and materials, including assignments, will be shared through our Canvas 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.
Learning Goals
The course seeks to contribute to student preparation for careers in biology, biotechnology, and health related fields, including further education in graduate and professional schools. It serves as an introduction to topics that show the pervasive role of large data analysis and management in the life sciences. Students will learn how to critically think about experiments involving tens of thousands of data points, as well as how record keeping, dissemination, and access control of such data have changed approaches to research, health care, and environmental issues in the digital age.
Assignments
The class material will be organized into seven topics (modules), each occupying on average four class periods over a two-week section. The first period of each section will give an overview of the topic. The subsequent periods will go into details and include question/answer time on homework problems.
Grading
Grades will be based on a traditional 100-point scale (roughly translating to letter grades in intervals of 5; i.e., 100 to 95 equals A+, 94 to 90 equals A, 89 to 85 equals A-, 84 to 80 equals B+, and so forth). The cumulative point score will be derived as the total of six homework assignment scores and a written final (which will count 28 points). The homework assignments will align with the modules and will be posted and graded as "quizzes" on Canvas.
Text book
Extensive class notes will be made available for strictly private use in the class. Other resources will be linked on our course schedule page.