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    BIOL L388 (offered as L410) Spring 2017

    Digital Biology: A survey of topics in bioinformatics and functional genomics

    BIOL L388 (offered as L410) Spring 2017

    Time & Location:    Tues, Thur 11:15a - 12:30p (Credits: 3.0); Global & International Studies (GA) 0013
    Instructors    Volker Brendel (205C Simon Hall; Tel.: 855-7074)
    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/2017/DBS17schedule.php

    btn_printerFriendly.gif version of this syllabus

    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, or Computers Science may find the course accessible and of interest. Prerequisite is BIOL 211 or 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 (chapters), each occupying four class periods over a two-week section. The first period of each section will give an overview of the topic. The second and third periods will go into details and include question/answer time on homework problems. There will be on average one graded homework assignment per chapter, which will ask students to solve mini-projects exploring the current topic in practice. These tasks can be done in groups, but each student must submit their own account of the solution. The fourth period for each chapter will consist of a written test (quiz). Each quiz will count at most 15 points towards the grade in the class (see below).

    Grading

    Grades will be based on a 100-point scale, derived as the total of the four best scores from the six quizzes, the homework score (20 points maximum), and a written final (which will also count 20 points). Absences during quizzes will be counted as zeros (and presumably discarded in calculating the final score).

    Text book

    The class is based on M. Zvelebil & J.O. Baum "Understanding Bioinformatics" (2007) Garland Science Textbook. An excellent resource for the class material is also provided by MITOPENCOURSEWARE's Foundations of Computational and Systems Biology. Relevant video links will be posted on our schedule.