Computational Systems Biology Main Page

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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.



BCB420 / JTB2020

These are the course pages for BCB420H (Computational Systems Biology). Welcome, you'll feel right at home here.


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 the Program has changed, and now our graduate students are usually quite competent at least in some practical aspects of computational biology. Not uniformly however, and the wide disparity of previous experience has made it increasingly difficult to provide course offerings that address students' needs. JTB2020 therefore shares its lecture components with BCB420 course, and there is a large range of topics in Applied Bioinformatics that are covered by students in self-study and discussion with the lecturer, customized to their actual needs.


The 2015 course...

This year's course will be very different from previous year's courses. In previous years we have worked with a structured, lecture-style format. This year we will be pursuing a wholly problem oriented format. This is the plan:

  • We'll identify an interesting challenge in computational systems biology
  • We'll formulate an approach to this challenge as a project
  • We'll define 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.[1]

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.

<!0-- Assignment 10 is active.
Ninth (and final) quiz in class: Wednesday, March 19., 14:00. Please don't forget your red pen for marking.
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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.


Submissions
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.


Recommended textbooks

Depending on your background, various levels of textbooks may be suitable. I will bring my evaluation copies to class so you can decide what may work for you.
Understanding Bioinformatics (Zvelebil & Baum) is a decent general introduction to many aspects of bioinformatics. It was published in 2007, an updated version is urgently needed. Still, some of the basics (like the algorithm for optimal sequence alignment) don't change. (Amazon) (Indigo) (ABE books)
Practical Bioinformatics (Agostino) covers some of the material of the BCH441 exercises. Expect a no-nonsense introduction to the very most basic stuff. I have my pet peeves about this book (as I have for many others, eg. why in the world do they still teach CLUSTAL when all available studies demonstrate it to be the least accurate MSA algorithm by a margin???), but if you haven't taken BCH441, this may serve you well. And if you did take BCH441, it may consolidate some ideas that I wasn't clear about. (Amazon) (Indigo) (ABE books)
If you are aware of recent good textbooks, or have your own opinions about these or other books, let me know.





Grading and Activities

Activity Weight
BCB410 - (Undergraduates)		 Weight
JTB2020 - (Graduates)
8 Self-evaluation and Feedback sessions 48 marks (8 x 6) 32 marks (8 x 4)
Class project contributions
  • 3 Tasks from the Task List (3 * 10 marks) (supersedes former Design and Implementation Categories)
  • Documentation (10 marks)
 40 marks 40 marks
Participation 12 marks 12 marks
Project Manuscript Draft   16 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...


Resources

Course related


Contents related


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Notes

  1. ↑ Only in case you are sick will you be excused. But in that case you must contact me before class.


 

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