Bioinformatics Main Page

BCH441 - Bioinformatics

Welcome to the BCH441 Course Wiki.

These wiki pages are provided to coordinate information, activities and projects in the introductory bioinformatics course taught by Boris Steipe at the University of Toronto. If you are not one of my students, you can still browse this site, however only users with a login account can edit or contribute or edit material. If you are here because you are interested in general aspects of bioinformatics or computational biology, you may want to review the Wikipedia article on bioinformatics, or visit Wikiomics. Contact boris.steipe(at)utoronto.ca with any questions you may have.

Assignment 5 has been posted.
Quiz on the assignment: Wednesday, October 17. in the tutorial session.

The Course

BCH441H1F is the undergraduate course code.
BCH1441H1F is the cross-listed course code for graduate students.

Organization

Dates

BCH441 is a Fall Term course.

Lectures: Tuesday, 16:00 to 17:00 and Wednesday, 15:00 to 16:00

Tutorial sessions: Wednesday, 14:00 to 15:00 for in-class quizzes, quiz debriefings, exam preparation and other activities, as the need arises.

Location

MSB 2173 (Medical Sciences Building)

General

See the Course Web page for general information.

We are recommending Understanding Bioinformatics, Zvelebil & Baum, Garland 2008 as a background textbook for the course. (buy used at AbeBooks)

This is an electronic submission only course; but if you must print material, you might consider printing double-sided. Learn how, at the Print-Double-Sided Student Initiative.

Grading and Activities

 

Activity	Weight BCH441 - (Undergraduates)	Weight BCH1441 - (Graduates)
12 In-class quizzes	42 marks (12 x 3.5)	24 marks (12 x 2)
Open project	28 marks (7 + 7 + 14)	28 marks
"Classroom" participation	10 marks	10 marks
Thesis Project		18 marks
Final exam	20 marks	20 marks
Total	100 marks	100 marks

A note on marking

It is not my policy to adjust marks towards a target mean and variance (i.e. there will be no "belling" of grades). I feel strongly that such "normalization" detracts from a collaborative and mutually supportive learning environment. If your classmate gets a great mark because you helped him with a difficult concept, this should never have the effect that it brings down your mark through class average adjustments. Collaborate as much as possible, it is a great way to learn. However I may adjust marks is if we phrase questions ambiguously on quizzes or if I decide that the final exam was too long.

 

Timetable and syllabus

 

I n t r o d u c t i o n

 

Week	Date	Topics	Activities	Assignment
1	Sept. 10 - 16	Bioinformatics focusses on the data and methods, and Computational Biology defines the objectives, to bring our understanding of Biology to a rigorous, principled, quantitative and predictive level. Over the last two decades, ever since bioinformatics began to take centre stage in the life sciences, the rate of change in the discipline has continuously accelerated. In part, driven by the growth of the Internet, in part through novel algorithms, but to the largest part driven through a very large increase in the volume and quality of data, opportunities for computational analysis in the life science lab have grown in leaps and bounds. One of the associated challenges is to keep abreast of the rapidly changing methods and tools that are available. This course focuses on the basic principles and concepts of the field and emphasis techniques and skills that are easily accessible and freely available to every life science researcher. Course Organisation Current bioinformatics Databases Services Tools -- Lecture slides 2012: 01 - Introduction Lecture recordings 2012: 01 - Introduction (mp4, 14.3 MB)	—	Assignment 1

 

D a t a  a n d  D a t a  A n a l y s i s

 

Week	Date	Topics	Activities	Assignment
2	Sept. 17 - 23	In principle, most of the data of interest to us is freely available on the Web, in public repositories. However, the number of databases and associated Web services is large and in constant flux and integrating the data has its own issues. The most important issue is to be clear about the abstractions we use and how they relate back to the biology they describe. Sequences Structures -- Lecture recordings 2012: 02 - Sequences (mp4, 23.0 MB) Lecture recordings 2012: 03 - Structure data (mp4, 18.1 MB)	Quiz 1	Assignment 2
3	Sept. 24 - 30	... Sequence analysis Machine learning -- Lecture recordings 2012: 04 - Sequence Analysis I (mp4, 12.8 MB)	Quiz 2, project concept due	Assignment 3
4	Oct. 1 - 7	... Protein structure interpretation Protein structure domains -- Lecture recordings 2012: 06 - Interpreting Protein Structure (mp4, 34.9 MB) Lecture recordings 2012: 07 - Protein Domains (mp4, 9.7 MB)	Quiz 3	Assignment 4

 

H o m o l o g y

 

Week	Date	Topics	Activities	Assignment
5	Oct. 8 - 14	... Homology principles Sequence alignment	Quiz 4, project outline due	Assignment 5
6	Oct. 15 - 21	... BLAST Multiple sequence alignment	Quiz 5	Assignment 6
7	Oct. 22 - 28	... Information theory BIO Statistics	Quiz 6	Assignment 7
8	Oct. 29 - Nov. 4	... Homology modelling Molecular dynamics Ab initio structure prediction	Quiz 7	Assignment 8

 

G e n o m e s

 

Week	Date	Topics	Activities	Assignment
9	Nov. 5 - 11	... Genome sequencing and annotation	Quiz 8	Assignment 9
10	Nov. 12 - 18	... Fall break - no class on Tuesday, Nov. 13 SNPs Human genomics	Quiz 9, project final submission due	Assignment 10

 

P h y l o g e n i e s

 

Week	Date	Topics	Activities	Assignment
11	Nov. 19 - 25	... Phylogenetic analysis principles Phylogenetic tree building	Quiz 10	Assignment 11
12	Nov. 26 - Dec. 2	... Phylogenetic data interpretation Functional annotation and Function prediction	Quiz 11	Assignment 12
-	Dec. 4	... Exam review	Quiz 12

 

Lecture slides 2012

None yet.