Spring 2021 - MBB 243 D100
Data Analysis for Molecular Biology and Biochemistry (3)
Class Number: 2643
Delivery Method: In Person
Course Times + Location:
Th 2:30 PM – 4:20 PM
REMOTE LEARNING, Burnaby
Prerequisites:MBB 222 and MATH 152 or MATH 155. STAT 201 (or an equivalent statistics course) or STAT 270 is recommended.
Introductory data analysis focusing on molecular biology data sets and examples and including basic programming skills using Python and basic statistics skills using R.
The purpose of this introductory data analysis course is to teach students in molecular biology or any students who will analyze molecular data, basic knowledge of molecular biology data types, data analysis methods including basic programming skills using Python, and basic statistics skills using R.
LecturesLecture 1 Molecular biology data and data analysis.
Lecture 2 Molecular sequences: features & composition.
Lecture 3 Gene splicing and GFF data format.
Lecture 4 Sequencing analysis using Biopython.
Lecture 5 Quantitative DNA analysis using Python conditional test.
Lecture 6 Searching for restriction sites in DNA sequences.
Lecture 7 Searching for sequence features in protein sequences.
Lecture 8 Genetic code and DNA translation.
Lecture 9 Quantitative analysis of genes using R.
Lecture 10 Analyzing genomics big data using R data frame.
Lecture 11 Genome annotation using R data frame and R graphics.
Lecture 12 Genome analysis using Bioconductor.
LabsLab 1Learning Python: printing and manipulating sequences.
Lab 2Reading and writing sequence files.
Lab 3Lists, loops, reading large sequence files.
Lab 4Writing our own functions for processing sequences.
Lab 5Quantitative DNA analysis using Python conditional test.
Lab 6Using regular expressions to search for sequence features in DNA sequences.
Lab 7Using regular expressions to search for sequence features in protein sequences.
Lab 8Translating DNA sequences using Python dictionaries.
Lab 9Learning R: molecular data analysis and presentation.
Lab 10Working with genome-scale sequences.
Lab 11Using R data frames and R graphics
Lab 12Technical review
- In class lab tasks: In each lab, there is a list of tasks that should be accomplished in class. Results are submitted by the end of each lab. 20%
- Lab assignments: Short assignments will be handed out in lab sessions and will be due at the start of your lab one week later, unless indicated otherwise. There is a 10% per day late penalty for assignments received after the due date time. 35%
- Midterm and Final exams - a mixture of multiple choice, short answer and written questions. (10% for midterm exam and 30% for final exam) 35%
- Participation 10%
Students with credit for CMPT 102, 120, 125, 126, 128 or 130 may not take this course for further credit.
Final exam: no
Remote invigilation: possibly
MATERIALS + SUPPLIES:
- access to high-speed internet
- computer with webcam
- specialized software: python biophython R
Python for Biologists. Martin Jones. 2013. CreateSpace Independent Publishing Platform.
Department Undergraduate Notes:
- For help with writing, learning and study strategies please contact the Student Learning Commons at
- Students requiring accommodations as a result of a disability, must contact the Centre for Accessible Learning (778-782-3112 or e-mail: firstname.lastname@example.org)
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
TEACHING AT SFU IN SPRING 2021
Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (email@example.com or 778-782-3112).