Fall 2020 - CMPT 441 D100
Computational Biology (3)
Class Number: 7061
Delivery Method: In Person
This course introduces students to the computing science principles underlying computational biology. The emphasis is on the design, analysis and implementation of computational techniques. Possible topics include algorithms for sequence alignment, database searching, gene finding, phylogeny and structure analysis. Students with credit for CMPT 341 may not take this course for further credit.
This is an introductory course on fundamental algorithmic techniques used to solve computational problems encountered in molecular biology. The course will investigate both traditional deterministic algorithms such as dynamic programming as well as machine learning and AI methods in Computational Biology. We will focus on practical algorithmic solutions as well as theoretical challenges. Students need to have access to a computer, web-cam, and mic and a sufficiently stable internet connection as most content will be delivered online. Lectures will be given in live mode with an opportunity for students to interact. Lectures will also be recorded and posted.
- Molecular biology basics
- Public Databases and Tools
- Sequence Analysis (local and global alignments)
- Multiple Sequence Alignments
- Dynamic Programming
- Markov Chains and Hidden Markov Models (HMMs)
- Sequence Similarity Search
- RNA secondary Structure Prediction
- Thermodynamic Models
- Machine Learning: Evolutionary Computation, Neural Networks
- There may be assignments, a midterm, a project and/or a final exam. Details will be discussed in class in the first week of classes. Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).
An Introduction to Bioinformatics Algorithms, Neil Jones and Pavel Pevzner, MIT Press, 2004,
- Biological Sequence Analysis: Probabilistic Models of Proteins & Nucleic acids, R. Durbin, S. Eddy, A. Krogh, G. Mitchison, Cambridge University Press, 1998, 9780521629713
- Bioinformatics: The Machine Learning Approach, Pierre Baldi, Sren Brunak, MIT Press, 2001, 9780262025065
- Algorithms on Strings, Trees, and Sequences, Dan Gusfield, Cambridge University Press, 1997, 9780521585194
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
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TEACHING AT SFU IN FALL 2020
Teaching at SFU in fall 2020 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 (firstname.lastname@example.org or 778-782-3112).