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Note that the information presented here does not necessarily reflect the most up to date syllabus or course information. Rather this information is intended to provide a general overview of course content from previous offerings.
Welcome to Binfo 300, "Algorithms in Bioinformatics". The course is part of the undergraduate bioinformatics program, though enrolment is not restricted to students in Bioinformatics. The prerequisites for Binfo 300 are Cmpt 280, Binfo 200, and one of BIOC 230, BIOL 226, or MCIM 216.
As this course is designed to be a another "capstone" course in the bioinformatics program, it integrates material in the life sciences, computational sciences, mathematics, probability theory and statistics. The course will explore more fully concepts introduced in Binfo 200 from an algorithmic or computer science perspective. This will include mathematical preliminaries, string matching algorithms, physical mapping theory and algorithms, algorithms for sequence alignment, sequence assembly, genome rearrangements, sequence analysis, phylogenetic analysis, RNA structure prediction, protein structure prediction and mass spectrometry. The level of treatment of material will be at a senior undergraduate computer science level; e.g. expect to have to create, modify and mathematically analyze algorithms. Also, expect to write real code. Students are expected to be familiar with C, C++, Java and Perl.
Ian McQuillan, Computer Science
email:
mcquillan @ cs (.usask.ca)
office: Thorv S423 (in the Spinks Addition)
telephone: 966-2900
| Class: | A reading class, will meet Tuesdays at 1:00p.m. | Room Thorv S341 |
|---|
Office hours are by appointment. Email is usually the best way to contact me.
Assignments, announcements, etc.. will be distributed by email.
We will try to follow the organization of the class text. However, some topics may be left out, and some topics may come from other resources. Note that we may not be able to get to all the topics in the text; how far we get will depend on our rate of progress.
The following table indicates the tentative organization of topics.
| Topic number | Topic |
|---|---|
| 1 | Introduction to the class |
| 2 | Basic Concepts: Strings, Graphs and Algorithms |
| 3 | String Algorithms |
| 4 | Alignment Methods |
| 5 | Physical Mapping |
| 6 | DNA Sequencing |
| 7 | Finding Signals in DNA Sequencing |
| 8 | Genome Rearrangements |
| 9 | Phylogenetic Trees |
| 10 | Haplotyping |
| 11 | Molecular Structures |
Some course material will be covered by assigned readings with follow-up in-class discussion. Lecture notes for the class may or may not be available in electronic form, depending on the topic area.
There will be assignments approximately weekly, to be completed on an individual basis.
| assigments and exercises | 60% |
| final exam | 40% |
The required textbook for the class is Algorithmic Aspects of Bioinformatics by Bockenhauer & Bongartz, 2007, published by Springer-Verlag. Copies should be in the Bookstore. (If not, please notify the instructor.)
The material for this class will be taken from a number of different textbooks, not just the one by Bockenhauer & Bongartz. These include
Protein Bioinformatics by Eidhammer & Jonassen & Taylor, 2004, published by Wiley.
An Introduction to Bioinformatics Algorithms by Jones & Pevzner, 2004, published by MIT Press.
Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis by Eidhammer, Jonassen, and Taylor, published by Wiley, 2003. Call No. QD431.25 .S85E53 2004.
Bioinformatics: Sequence and Genome Analysis, 2nd edition, by Mount, published by Cold Spring Harbor Press, 2004. Call No. QH 441.2 .M68 2004
Introduction to Computational Molecular Biology by Setubal and Meidanis, PWS Publishing, 1997. Call No. QH506 .S4893 1997.
Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids by Durbin, Eddy, Krogh, and Mitchison, Cambridge University Press, 1998. Call No. QP620 .B576 1998.
Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology by Gusfield, Cambridge University Press, 1997. Call No. QA76.9 .A43G87.
Statistical Methods in Bioinformatics by Ewens and Grant, Springer Verlag, 2001. Call No. R858 .E988 2001.
For those students who want to "brush up" on their bioinformatics background in preparation for this course, an excellent book is Fundamental Concepts of Bioinformatics by D. E. Krane and M. L. Rayner, 2003, Benjamin Cummings. This book is also on Reserve, with Call No. QH324.2 .K72 2003.
The University libraries have a large collection of books covering the area of bioinformatics. Students are encouraged to make use of them.
The main computational resources for this course will be the Computer Science LINUX labs in rooms Thorv S315 (north half), S320, and S360 (north half). Typically, non-proprietory software will be used in this course, such as gcc and EMBOSS. Programming languages used will be Java, C/C++, and Perl.
Below is an initial set of on-line bioinformatics resources that might be helpful in the class.
We encourage collaboration and research, but any form of plagiarism is unacceptable. Please take a look at the website below for detailed information on the department's policy: http://orb.usask.ca/undergraduate_studies/ugrad_academic_hon.php. The policy tries to show you what is and is not acceptable. We use sophisticated software to analyze assignments for plagiarism, and this software is very good at catching it. Please do not make the mistake of thinking you can get away with copying. We catch dozens of students every year.
