BIOL-L/MLS-M 388/BIOL-Z 602 Spring 2025

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

BIOL-L/MLS-M 388/BIOL-Z 620 Spring 2025

Time & Location:    Tues, Thur 11:30a - 12:45p (Credits: 3.0); Biology Building (JH) 001
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/DBS25schedule.php

HTML 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, Informatics, Data and Computer Science may find the course accessible and of interest. As of Spring 2024, the course includes a graduate credit section appropriate for Ph.D. students in Biology and related fields who seek how-to knowledge in bioinformatics approaches. Prerequisite for the class is BIOL 211 or an equivalent course or permission of the instructor, as well as a basic knowledge of concepts in probability and statistics. 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. Please pay keen attention to the following:

Sexual Misconduct & Title IX: Indiana University policy prohibits sexual misconduct in any form, including sexual harassment, sexual assault, stalking, sexual exploitation, and dating and domestic violence. If you have experienced sexual misconduct, or know someone who has, the University can help. If you are seeking help and would like to speak to someone confidentially, you can make an appointment with the IU Sexual Assault Crisis Services at (812) 855-5711, or contact a Confidential Victim Advocate at (812) 856-2469 or cva@indiana.edu. It is also important that you know that University policy requires instructors to share certain information brought to their attention about potential sexual misconduct, with the campus Deputy Sexual Misconduct & Title IX Coordinator or the University Sexual Misconduct & Title IX Coordinator. In that event, those individuals will work to ensure that appropriate measures are taken and resources are made available. Protecting student privacy is of utmost concern, and information will only be shared with those that need to know to ensure the University can respond and assist. Please visit http://stopsexualviolence.iu.edu/ to learn more.

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 the best five of seven homework assignment scores (each worth a maximum of 15 points) and a final project/quiz submission (which will count a maximum of 20 points). The homework assignments will align with the modules and will be posted and graded as “quizzes” on Canvas. The final project will involve designing and running a typical (although small-scale) bioinformatics workflow that will rely on many of the tools and approaches discussed in class. Expectations will be scaled appropriate to the student status (graduate students may select a project of their research interest). In order to achieve our learning goals, students are expected to attend and participate regularly in class meetings and all assignments. A maximum of 5 points will be given for participation.

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.

Important Footnotes

Academic Integrity: As a student at IU, you are expected to adhere to the standards contained in the Code of Student Rights, Responsibilities, and Conduct (the Code). Academic misconduct is defined as any activity that tends to undermine the academic integrity of the institution. Academic integrity violations include: cheating, fabrication, plagiarism, interference, violation of course rules, and facilitating academic dishonesty. When you submit an assignment with your name on it, you are signifying that the work contained therein is yours, unless otherwise cited or referenced. Any ideas or materials taken from another source must be fully acknowledged. Students should not share their work with any other students. If plagiarism or other cheating occurs, both students involved will be considered responsible even if the student sharing their work was unaware that academic misconduct would occur or had occurred. Ignorance of what constitutes academic misconduct or plagiarism is not a valid excuse. In addition, posting questions from quizzes/exams or assignments or downloading answers from online sources is considered academic misconduct. All suspected violations of the Code will be reported to the Dean of Students (Office of Student Conduct) and handled according to University policies. Sanctions for academic misconduct in this course may include a failing grade on the assignment, a reduction in your final course grade, or a failing grade in the course, among other possibilities. If you are unsure about the expectations for completing an assignment or taking a test or exam, be sure to seek clarification from your instructor in advance.

Note Selling: Various commercial services have approached students regarding selling class notes/study guides to their classmates. Selling the instructor’s notes/study guides or uploading course assignments to these sites in exchange for access to materials for other courses is not permitted. Violations of this policy will be reported to the Dean of Students (Office of Student Conduct) as academic misconduct (violation of course rules). Sanctions for academic misconduct for this action may include a failing grade on the assignment for which the notes/study guides or assignments are being uploaded, a reduction in your final course grade, or a failing grade in the course, among other possibilities. Additionally, you should know that selling a faculty member’s notes/study guides individually or on behalf of one of these services using IU email, or via Canvas may also constitute a violation of IU information technology and IU intellectual property policies; additional consequences may result.

Online Course Materials: The instructor teaching this course holds the exclusive right to distribute, modify, post, and reproduce course materials, including all written materials, study guides, lectures, assignments, exercises, and exams. Some of the course content may be downloadable, but you should not distribute, post, or alter the instructor’s intellectual property. While you are permitted to take notes on the online materials and lectures posted for this course for your personal use, you are not permitted to re-post in another forum, distribute, or reproduce content from this course without the express written permission of the instructor.

GroupMe: Please note that you may receive emails from other students about joining GroupMe for individual classes via Canvas. Even though invitations to join the group may be issued through Canvas, they do not imply the endorsement of the course instructor. While GroupMe can be an effective tool for keeping in touch with classmates and clarifying information related to the course, it can also be source of unauthorized information sharing or collaboration among students. Collaborative efforts on assignments, quizzes and exams, including sharing or discussing answers when the instructor has not expressly authorized collaboration is considered cheating, If academic dishonesty occurs via GroupMe, everyone involved in the thread may be found responsible for academic misconduct since membership in the group suggests that that they have been able to view the information shared.