CSI 5126 (COMP 5108). Algorithms in Bioinformatics

Marcel Turcotte
University of Ottawa
School of Electrical Engineering and Computer Science (EECS)
Marcel.Turcotte@uottawa.ca

Fall 2017

[ PDF ]

Course Hours

The first lecture will be held on September 6, 2017. Information about the schedules, tutorials, lecture notes, etc. can be found on the course web page.

Professor

Calendar Description

Fundamental mathematical and algorithmic concepts underlying computational molecular biology; physical and genetic mapping, sequence analysis (including alignment and probabilistic models), genomic rearrangements, phylogenetic inference, computational proteomics and systemic modeling of the whole cell. Prerequisites: CSI 3105, COMP 3804 or equivalent.

Course Learning Outcomes

Upon completion of the course, student will be able to:

Course Calendar

  1. Syllabus and introduction, course objectives and students expectations.
  2. Essential cell biology.
    Wiesława Widłak (2013). Molecular Biology: Not Only for Bioinformaticians (Vol. 8248). Springer. Chapters 1, 2, and 3.
  3. Essential Cell Biology.
    Wiesława Widłak (2013). Molecular Biology: Not Only for Bioinformaticians (Vol. 8248). Springer. Chapters 4, 5, and 9.
  4. Suffix Trees.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 43-53.
    Dan Gusfield (1997) Algorithms on strings, trees, and sequences : computer science and computational biology. Cambridge University Press. Chapters 5, 6 (optional), 7.
  5. Suffix Trees.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 43-53.
    Dan Gusfield (1997) Algorithms on strings, trees, and sequences : computer science and computational biology. Cambridge University Press. Chapters 8 (optional), 9.
  6. No lecture on Friday, September 22, 2017.
  7. Molecular Sequence Alignment.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 11-15, 30-33.
  8. Molecular Sequence Alignment.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 35-39.
  9. Substition Matrices.
    Warren J. Ewens, Gregory R. Grant (2001) Statistical Methods in Bioinformatics: An Introduction. Springer. Pages: 238-249.
  10. Inferring Phylogenies.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 143-168.
  11. Inferring Phylogenies.
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 143-168.
  12. Examination.
  13. Student presentations of scientific publications.
  14. Student presentations of scientific publications.
  15. Student presentations of scientific publications.
  16. RNA Secondary Structure. Dynamic programming.
  17. RNA Secondary Structure. Cocke-Younger-Kasami.
  18. Sequence Motif (Median).
  19. Sequence Motif (Hidden Markov Model).
    Bernhard Haubold and Thomas Wiehe (2006). Introduction to computational biology: an evolutionary approach. Birkhäuser Basel. Pages 101-116.
  20. MotifGP.
  21. ModuleInducer.
  22. Students presentations on their projects.
  23. Students presentations on their projects.
  24. Students presentations on their projects.

Evaluations

Oral Presentations

Papers in (refereed) journals and conference proceedings are the main vehicules for communicating scientific information. You must select a publication that presents either a specialized application or a more efficient algorithm on the topic of string matching, which has been presented in class, in the weeks preceding the presentations.

Objectives

Deliverable

Project

Objectives

Deliverable

The format of the projects is quite flexible. I foresee three broad types of work: the development of a novel application, the analysis of a new data set, or a (thorough) review of the literature on a specific topic. For all three types of work, I would like to see a review of the literature, sample data and a prototype implementation (where applicable). The main difference between each type of work will be the relative importance of each of the components.

Teamwork

Teams will be made of 1 or 2 members. Larger teams will have to produce proportionally more work! Complementary work between teams is also welcomed, i.e. two or more teams working on a related but complementary topic, leading to a more realistic application.

Report

Reports should be sufficiently detailed that it should be possible to implement the approach on the basis of the text alone. Having said that, you should also make every conceivable effort to keep the report concise. Assuming a team of size 2, a 10–15 page report should be appropriate. Structure for the reports:

Material and Resources

Lecture notes (slides) and complementary resources will be posted on the Web.

References

Although there are no required textook, these monographs are part of my short list of essential bioinformatics books.

Monographs

Documents on the Web

Springer Link provides our community with access to journals, books, series, protocols and reference documents (access restricted to University of Ottawa based on your IP address).

Essential Cell Biology

Plagiarism

Academic fraud is an act by a student that may result in a false evaluation (including papers, tests, examinations, etc.). It is not tolerated by the University. Any person found guilty of academic fraud will be subject to severe sanctions.

Here are some examples of academic fraud:

An individual who commits or attempts to commit academic fraud, or who is an accomplice, will be penalized. Here are some examples of possible sanctions:

Student Services

Academic Writing Help Centre

At the AWHC you will learn how to identify, correct and ultimately avoid errors in your writing and become an autonomous writer.

In working with our Writing Advisors, you will be able to acquire the abilities, strategies and writing tools that will enable you to:

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About the Instructor

I have been conducting research in bioinformatics since 1989. I am particularly interested in the inference of structural motifs, mostly for ribonucleic acids.