Computational Systems Biology Main Page

Computational Systems Biology

Course Wiki for BCB420 (Computational Systems Biology) and JTB2020 (Applied Bioinformatics).

This is our main tool to coordinate information, activities and projects in University of Toronto's computational systems biology course BCB420. If you are not one of our 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.

Warning – this page and all associated course pages currently under intense revision. (2016-12-17)

BCB420 / JTB2020

These are the course pages for BCB420H (Computational Systems Biology). Welcome, you're in the right place.

These are also the course pages for JTB2020H (Applied Bioinformatics). How come? Why is JTB2020 not the graduate equivalent of BCB410 (Applied Bioinformatics)? Let me explain. When this course was conceived as a required part of the (then so called) Collaborative PhD Program in Proteomics and Bioinformatics in 2003, there was an urgent need to bring graduate students to a minimal level of computer skills and programming; prior experience was virtually nonexistent. Fortunately, the field has changed and our current graduate students are usually quite competent at least in some practical aspects of computational biology. In this course we profit from the rich and diverse knowledge of the problem-domain our graduate students have, while bringing everyone up to a level of competence in the practical, computational aspects.

The 2017 course...

In this course we pursue a wholly problem oriented format:

• We start from an interesting challenge in computational systems biology;
• We'll formulate an approach to this challenge as a project, defining the the resources we need – data sources, algorithms, programming- and collaboration support
• We'll define students' roles in the project according to their skills and experience
• Then we will implement the project.

Organization

First lecture this term: Tuesday, January 10. 2017 at 16:00 (4 pm), MSB 4171.

Attendance in person at the first lecture is mandatory. You will loose three participation marks if you are not present in person.

This may seem silly but it is unfortunately necessary - I can't get this course started effectively if you are not present when we work out the organization of the course, sign you up to mailing list and Student Wiki, and discuss the syllabus for this term.

Dates

BCB420/JTB2020 is a Winter Term course.

Lectures: Tuesdays, 16:00 to 18:00. (Classes start at 10 minutes past the hour.)

Exam: None for this course.

Location

MS 4171 (Medical Sciences Building).

Departmental information

For BCB420 see the BCB420 Biochemistry Department Course Web page.

For JTB2020 see the JTB2020 Course Web page for general information.

Preparation

Undergraduate students in this course will often have taken my BCH441 course; graduate students come from a wide variety of backgrounds. The course requires (i) a solid understanding of molecular biology, (ii) introductory level knowledge of bioinformatics, (iii) a working knowledge of the 'R programming language. I am only weakly enforcing prerequisites, they are basically your own responsibility. Knowledge of molecular biology is something you have to acquire on your own and bring to class. If you are comfortable reading the introductory literature listed below, and understanding the biology, you should be good to go.

The preparation material detailed will be the subject of our first Quiz in the second week of class. You may find it challenging to adequately prepare yourself in just one week. Please have a look at the three topics below in order to get a head start.

• A working knowledge of R

• Work through the R tutorial on this site and complete the tasks and exercises in the tutorial and the associated scripts.

• A basic knowledge of Bioinformatics

• A list of detailed tutorials will be posted here around Jan. 1. 2017.

• Project specific prereading

Read the following papers:

Grading and Activities

 

Activity	Weight BCB410 - (Undergraduates)	Weight JTB2020 - (Graduates)
5 Self-evaluation and Feedback sessions("Quiz")	40 marks (5 x 9)	30 marks (5 x 6)
Class project contributions A maximum of 45 marks combined, for tasks from the Project Task List	45 marks	45 marks
Participation	15 marks	15 marks
Contribution to Project Manuscript Draft		10 marks
Total	100 marks	100 marks

A note on marking

I do not 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.

Prerequisites

You must have taken an introductory bioinformatics course as a prerequisite, or otherwise acquired the necessary knowledge. Therefore I expect familiarity with the material of my BCH441 course. If you have not taken BCH441, please update your knowledge and skills before the course starts. I will not make accommodations for lack of prerequisites. Please check the syllabus for this course below to find whether you need to catch up on additional material, and peruse this site to find the information you may need. A (non-exhaustive) overview of topics and useful links is linked here.

Timetable and syllabus

Syllabus and assignments will still be in flux for a few weeks.

 

PREPARATION

 

Week	In class: Tuesday, Jan. 12	Readings	Assignment	In class: Tuesday, Jan. 19
1	Syllabus Projects Important dates Grading Organization Signup to mailing list and Student Wiki. Defining biological Systems	R Tutorial	Assignment 1	Perspectives: Customizing R and R Studio. Subsetting and filtering of vectors, arrays and lists.

 

COLLABORATION

 

Week	In class: Tuesday, Jan. 19	Readings	Assignment	In class: Tuesday, Jan. 26
2	Collaboration tools Defining the class project	TBD	Assignment 2	Perspectives ... TBD.

 

CODE

 

Week	In class: Tuesday, Jan. 26	Readings	Assignment	In class: Tuesday, Feb. 2
3	Data sources and workflows	TBD	Assignment 3	Self-evaluation & Feedback: Session 1 Perspectives ... TBD.

 

DEVELOPMENT

 

Week	In class: Tuesday, Feb. 2	Readings	Assignment	In class: Tuesday, Feb. 9
4	Development principles	TBD	Assignment 4	Self-evaluation & Feedback: Session 2 Perspectives ... TBD

 

GRAPHS

 

Week	In class: Tuesday, Feb. 9	Readings	Assignment	(In class): Tuesday, Feb. 23
5	Expressing biological relationships as graphs. Introduction to graph theory Graph measures Graphs in R. Multigraphs and hypergraphs. Note: No class on the following Tuesday, February 16 (Reading Week).	TBD	Assignment 5	Note: No in-class meeting on that date. Perspectives ... TBD

 

REGRESSION

 

Week	(In class): Tuesday, Feb. 23	Readings	Assignment	In class: Tuesday, March 1
6	Note: No in-class meeting on that date. Linear and non-linear regression.	TBD	Assignment 6	Self-evaluation & Feedback: Session 3 Perspectives ... TBD

 

INFORMATION

 

Week	In class: Tuesday, March 1	Readings	Assignment	In class: Tuesday, March 8
7	Project status review	TBD	Assignment 7	Self-evaluation & Feedback: Session 4 Perspectives ... TBD

 

FEATURES

 

Week	In class: Tuesday, March 8	Readings	Assignment	In class: Tuesday, March 15
8	Note: March. 13 - Drop Date for the course. Gene regulatory networks revisited	TBD	Assignment 8	Self-evaluation & Feedback: Session 5 Perspectives ... TBD

 

CLUSTERING

 

Week	In class: Tuesday, March 15	Readings	Assignment	In class: Tuesday, March 22
9	Introduction to information theory. Application to semantic similarity measures for GO.	TBD	Assignment 9	Self-evaluation & Feedback: Session 6 Perspectives ... TBD

 

CLASSIFICATION

 

Week	In class: Tuesday, March 22	Readings	Assignment	In class: Tuesday, March 29
10	Clustering concepts - how to construct sets of related elements from similar features. Hierarchical clustering. Partition clustering. Graph clustering. Cluster quality.	TBD	Assignment 10	Self-evaluation & Feedback: Session 7 Perspectives ... TBD

 

INTEGRATION

 

Week	In class: Tuesday, March 29	Readings	Assignment	In class: Tuesday, April 5
11	Integrating project elements.	TBD	Assignment 11	Self-evaluation & Feedback: Session 8 Perspectives ... TBD

 

DOCUMENTATION

 

Week	In class: Tuesday, April 5	Readings
12	Presentation and documentation of results.	TBD

 

In depth...

• Glossary
• Mutation Data Matrices
• Amino acids

Resources

Course related

• Prerequisites for the course
• Student Wiki
• The Course Google Group.
• Netiquette for the Group mailing list

Contents related

• The VMD tutorial
• A Stereo Vision tutorial

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Notes