BMI633_S22

Instructor:  Sujin Kim


Course: BMI 633 (Section 201) - Syllabus
Introduction to Bioinformatics
Update: 1/10/2022
Term: Spring 2022
Credit hours: 3 credits

Meeting days/time/location:
• Mondays and Wednesdays/1:00 pm - 2:30 pm/Multidisciplinary Science Building (MDS) Rm.221
• Canvas (asynchronous, unless notified); course materials will be posted including assignments, exams, slides, data, files, etc. https://uk.instructure.com/courses/2028119
Instructor Information

Name: Sujin Kim
Email: sujinkim@uky.edu
Office building and room number: Multidisciplinary Science Building (725 Rose Street) Room: 230F
Office phone: (859) 218-0110
Office hours:
1. Virtual office hours: Mondays 10a-11a by appointment via Zoom https://uky.zoom.us/j/87070402017 (Note: In-person office hour can be arranged by appointment, if necessarily.)
2. Preferred method of communication: Email: sujinkim@uky.edu
3. Maximum timeframe for responding to student communications: within 24 hours

Course Description
This is an introductory course aimed at a multi-disciplinary audience with an interest in applying the principles of information sciences for obtaining insight into biological processes and systems that can eventually be used to make informed decisions.

Course Prerequisites
Undergraduate level courses in Life Sciences, Computer Programming, Statistics, and Mathematics are desirable. Appreciation for life sciences as well as information sciences with a desire to learn in a multidisciplinary environment.

Required Materials
Compeau, Phillip & Pevzner, Pavel (2018). Bioinformatics Algorithms: an Active Learning Approach. 3rd edition. Published by Active Learning Publishers, LLC.
“This is the third edition of Bioinformatics Algorithms: an Active Learning Approach, one of the first textbooks to emerge from the revolution in online learning. A light hearted and analogy filled companion to the authors' acclaimed online courses, this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of both biology and
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computer science. Each chapter begins with a biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind, a popular platform for learning bioinformatics through programming.” Excerpted from the book.
Online access via Stepik: https://stepik.org/join-class/27155b1376c323ab4f943d6f23f986bca88a2966

Associated Expenses
Textbook
• online: https://stepik.org/course/55789/promo ($89)
• Hardcopy: Amazon https://www.amazon.com/BIOINFORMATICS-ALGORITHMS-Phillip-Compeau/dp/0990374637/ref=asc_df_0990374637/?tag=hyprod-20&linkCode=df0&hvadid=266033622375&hvpos=&hvnetw=g&hvrand=5950723980528839528&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9014319&hvtargid=pla-571925442395&psc=1 ($99.95)

Activities Outside of Regular Class Meetings
Not applicable
Skill and Technology Requirements
For technical/account help, students can contact Information Technology Services by phone 859-218-HELP (4357) and via the ITS Customer Services page. (https://www.uky.edu/its/customer-support-student-it-enablement/customer-services)
For course-related technological skills, assignment guidelines will be provided.

Student Learning Outcomes
A student in this course will be able to:
• Utilize basic biological understanding and computational skills to understand genetic modeling,
• Apply various software effectively to extract information from large genetic databases and to use this information in computational modeling,
• Develop problem-solving skills, including the ability to develop new computational algorithms and analytic approaches, and
• Understand the intersection of life and information sciences, the core of shared concepts, language, and skills the ability to speak the language of structure-function relationships, information theory, gene expression, and database queries.


Course Details

Tentative Course Schedule
Weeks
Topics
Notes
Lecture 1
1/10/2022(M)
About this class
-Syllabus, Course logistics, Q/A
Lecture 2
1/12/2022(W)
Bioinformatics Overview
(Biological Databases)
1/17/2022(M)
Martin Luther King Birthday - Academic Holiday
NO CLASS
Lecture 3(W)
1/19/2022
Essentials of molecular biology
Dr. Jong-Cheol Jeong
Lecture 4(M)
1/24/2022
Essentials of sequencing technology
Dr. Jong-Cheol Jeong
Lecture 5(W)
1/26/2022
Review sequencing technology tools: NCBI, FASTQC, etc.
Dr. Jin Chen
(tentative)
Lecture 6(M)
1/31/2022
Where in the genome does DNA replication begin?
(Compeau&Pevzner, ch.1 – part I)
Lecture 7(W)
2/2/2022
Where in the genome does DNA replication begin?
(Compeau&Pevzner, ch.1 – part II)
Lecture 8(M)
2/7/2022
Which DNA patterns play the role of molecular clocks? (Compeau&Pevzner, ch.2 – part I)
Lecture 9(W)
2/9/2022
Which DNA patterns play the role of molecular clocks?
(Compeau&Pevzner, ch.2 – part II)
Lecture 10(M)
2/14/2022
Sequence Alignment I
Lecture 11(W)
2/16/2022
Sequence Alignment II
Lecture 12(M)
2/21/2022
How do we assemble genomes?
(Compeau&Pevzner, ch.3 – part I)
Lecture 13(W)
2/23/2022
How do we assemble genomes?
(Compeau&Pevzner, ch.3 – part II)
Lecture 14(M)
2/28/2022
DNAseq Analysis Pipelines on Galaxy
Lecture 15(W)
3/2/2022
Metagenomics
Dr. Jinpeng Liu
3/7/2022(M)
Review Week (~Lecture 15)
3/9/2022(W)
Midterm Exam
3/14/2022(M)
Spring Vacation – Academic Holiday
NO CLASS
3/16/2022(W)
Spring Vacation – Academic Holiday
NO CLASS
Lecture 16(M)
3/21/2022
How do we sequence antibiotics?
(Compeau&Pevzner, ch.4 – part I)
GWAS
Lecture 17(W)
3/23/2022
How do we sequence antibiotics?
(Compeau&Pevzner, ch.4 – part I)
Dr. Jin Chen
(tentative)
Lecture 18(M)
3/28/2022
How do we compare biological sequence?
(Compeau&Pevzner, ch.5 – part I)
Lecture 19(W)
3/30/2022
How do we compare biological sequence?
(Compeau&Pevzner, ch.5 – part II)
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Course Activities and Exams
(30%) Practical exercises
(40%) Exams
(20%) Presentation
(10%) Attendance and Participation

Grading Scale
90 – 100% = A
80 – 89% = B
70 – 79% = C
Below 70%= E

Attendance Policy/Acceptable Documentation
Attendance, excused absences, and make-up opportunities for this course will conform to the course policies established by the Office of Academic Ombud Services as found at https://www.uky.edu/ombud/
For excused absence, acceptable documentation such as a letter from an institution or healthcare provider, or published information is required. Penalties for unexcused absences will be applied to grading in the attendance and participation.

Assignment Policies
Assignment Submissions
Assignments are asked to submit via Canvas Assignment links. Email attachment is not permitted, unless approved. Further instruction will be posted in Canvas.
Lecture 20(M)
4/4/2022
Gene Expression I, II
Lecture 21(W)
4/6/2022
Differential gene expression
Dr. Jong-Cheol Jeong
Lecture 22(M)
4/11/2022
scRNAseq-1: Serut, Monocle
Lecture 23(W)
4/13/2022
scRNAseq-2: scDGN
Lecture 24(M)
4/18/2022
Clinical Informatics
Dr. Cody Baumgardner
(tentative)
Lecture 25(W)
4/20/2022
Gene set enrichment analysis I
Lecture 26(M)
4/25/2022
Gene set enrichment analysis II
Lecture 27(W)
4/27/2022
Cancer Genomics
Dr. Eric Durbin (tentative)
5/2/2022(M)
Review Week (Lectures 16 ~ 27)
5/4/2022(W)
Final Exam

Returning Assignments to Students
Unless further notice, you will receive your assignment grades within 2 weeks.

Late Assignments
Exercises that are turned in late will be marked one letter grade lower unless prior approval from the instructor has been obtained. It will be based on the time stamp provided by Canvas. (NOTE: Exercises more than one week past the original due date will not be graded, unless you receive permission from instructor.)

Academic Policy Statements
Senate’s Academic Policy Statements is available for your review at: https://www.uky.edu/universitysenate/acadpolicy.
Academic Offenses (Cheating, Plagiarism, and Falsification or Misuse of Academic Records)
Please refer to the Senate-maintained web page of Rules Regarding Academic Offenses (URL: https://www.uky.edu/universitysenate/ao).

Diversity, Equity, and Inclusion
The University of Kentucky is committed to our core values of diversity and inclusion, mutual respect and human dignity, and a sense of community (Governing Regulations XIV). We acknowledge and respect the seen and unseen diverse identities and experiences of all members of the university community (https://www.uky.edu/regs/gr14). These identities include but are not limited to those based on race, ethnicity, gender identity and expressions, ideas and perspectives, religious and cultural beliefs, sexual orientation, national origin, age, ability, and socioeconomic status. We are committed to equity and justice and providing a learning and engaging community in which every member is engaged, heard, and valued.
We strive to rectify and change behavior that is inconsistent with our principles and commitment to diversity, equity, and inclusion. If students encounter such behavior in a course, they are encouraged to speak with the instructor of record and/or the Office of Institutional Equity and Equal Opportunity. Students may also contact a faculty member within the department, program director, the director of undergraduate or graduate studies, the department chair, any college administrator, or the dean. All of these individuals are mandatory reporters under University policies.
Senate Council-approved Syllabus Statement on Diversity, Equity, and Inclusion (DEI). (https://www.uky.edu/universitysenate/syllabus-dei)]

Further Resources

Student Resources:
• UK's Tutoring and Coaching Resources
• Student Academic Support: https://www.uky.edu/studentacademicsupport/free-tutoring-and-coaching-resources)]
• The University offers a variety of resources to students. Visit the University Senate’s Resources Available to Students to access that list (https://www.uky.edu/universitysenate/student-resources).

Technical Requirements (Adopted from Distance Learning Recommendation, in case we are online.):
• “In order to have a successful educational experience in distance learning courses, there are minimum technology requirements that should be met. The University of Kentucky strongly recommends that each student purchase a personal computer. To review minimum recommendations and guidelines for your computer click here. University of Kentucky distance learning students are also encouraged to acquire the following hardware, software, and Internet connection to ensure that all systems used by distance learning courses will function properly.” Go to the link at: https://uky.service-now.com/techhelp?id=kb_article&sysparm_article=KB0012251&sys_kb_id=a6506d4cdb564c187d4c9ac5db96192e to test your network speed and other necessarily technology requirements for this class.
• UK Virtual Den: UK uses Citrix technologies to provide a portal for students to access a number of software packages that are used in student courses. It allows access to software and desktops anytime from anywhere. To access software, you can go to a computer lab, or use your own mobile device or personal computer. https://www.uky.edu/its/customer-support-student-it-enablement/classroom-av-support-student-technology-services/virtual-den

Information on Distance Learning Library Services
• Available at: http://libraries.uky.edu/dlls
• Carla Cantagallo, DL Librarian, (859) 218-1240
• Email: dllservice@email.uky.edu
• DL Interlibrary Loan Service: http://libraries.uky.edu/page.php?lweb_id=253
Information on Libraries and Canvas
• UK Libraries at: https://libraries.uky.edu/page.php?lweb_id=1020
• MCL Homepage: http://libraries.uky.edu/MCL
• MCL classes: http://libraries.uky.edu/libpage.php?lweb_id=33&llib_id=12
• Off-Campus Access Instructions (Proxy Help): http://libraries.uky.edu/page.php?lweb_id=16
• Canvas login: https://www.uky.edu/canvas/
• University of Kentucky-Online Program: https://www.uky.edu/academics/online-programs
• Canvas for Students (CNVS101): https://uk.instructure.com/courses/1096339

Contact information for:
• UK Information Technology Customer Service Center http://www.uky.edu/ukit/

Technical Issues
• Students should contact the instructor (via email) and the UKIT help desk in case they are unable to access the materials (http://www.uky.edu/UKIT, 859-218-HELP) so that issues can be resolved in a timely fashion and homework can be submitted on time.

Center for Computational Sciences