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.
Contents
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.
Every week will have a set of general and specific tasks. The general tasks will include background reading, installing software and familiarizing yourselves with websites and tools. These will the topics of the weekly short quizzes. The rest of the classroom time will be dedicated to discussion of progress on your specific tasks, open discussion of any arising issues, and definition of next week's tasks. All students are requested to be familiar with the entire breadth of the project and through this cover the individual course objectives that are detailed below.
Organization
First lecture this term: Wednesday, January 7. 2015 at 14:00 (2 pm), MSB 4279.
We will coordinate the organization of the course, sign you up to mailing list and Student Wiki, and discuss the (significant!) syllabus changes for this term.
Do not miss the first lecture - your input will be important and there is no good way for you to make up if you are not present.
- Dates
- BCB420/JTB2020 is a Winter Term course.
- Lectures: Wednesdays, 14:00 to 16:00. (Classes start at 10 minutes past the hour.)
- Exam: None for this course.
- Location
- MS 4279 (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
Exercises for the course will be linked from Assignment Pages. I expect everyone to complete them, however there will be no required submissions for exercises. Exercise-related questions as well as pre-reading related questions will be part of the weekly quizzes. Don't expect to do well on the quizzes unless you have done the exercises and completed the pre-reading carefully. This course demands a lot of your discipline and time-management. A large portion of your grade will be contributed by the Open Project. JTB2020 students will also complete a number of Applied Bioinformatics Exercises. Deliverables for the course will be completed well before end-of-term crunch time and there will be no final exam.
| Activity | Weight BCB410 - (Undergraduates) |
Weight JTB2020 - (Graduates) |
| 9 In-class quizzes | 54 marks (9 x 6) | 36 marks (9 x 4) |
| Class project contributions | 30 marks | 30 marks |
| "Classroom" participation | 16 marks | 16 marks |
| Applied Bioinformatics Exercises | 18 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. I may however adjust marks is if I phrase questions ambiguously on quizzes.
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.
Exercises and Pre-reading
All course units will have associated exercises that are topics for the following week's quiz.
All course units will have assigned pre-readings that are topics for the current week's quiz.
Timetable and syllabus
- Subject to change on short notice...
Under construction...
| I n t r o d u c t i o n | ||||
| Week | Date | Topics | Activities | Assignment |
| 1 | Jan. 6 – 12 |
Computational Biology aims to bring biology from its descriptive beginnings to a truly predictive science, based on consistent and well understood principles. In the systems biology field of computational biology, we deal primarily with large-scale, cross-sectional data, its relationships and hierarchies.
|
— | Assignment 1 |
| D a t a | ||||
| Week | Date | Topics | Activities | Assignment |
| 2 | Jan. 13 - 19 |
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 the question of how to define function and make this concept computable; from this arises the central role that ontologies play in the field.
|
Quiz 1 | Assignment 2 |
| 3 | Jan. 20 - 26 |
The large volume of data in any given systems biology experiment basically precludes the manual, gene-by-gene analysis of results. Questions arise regarding computational strategies for gene lists, especially the statistical tools and strategies we have at our disposal, and a minimum set of programming and automation skills.
|
Quiz 2 | Assignment 3 |
| "-omics" | ||||
| Week | Date | Topics | Activities | Assignment |
| 4 | Jan. 27 - Feb. 2 |
Genome sequencing brought the first complete overview of the information underlying life; the associated concept of the transcriptome - a description of which portion of the genome is expressed at what time - is the most basic functional description of this information.
|
Quiz 3, Open Project vision due in class | Assignment 4 |
| 5 | Feb. 3 - 9 |
Many more holistic, or cross-sectional descriptions of the molecular composition and assembly of the cell are being worked on.
|
Quiz 4 | Assignment 5 |
| I n t e r a c t i o n s , P a t h w a y s a n d N e t w o r k s | ||||
| Week | Date | Theme | Activities | Assignment |
| 6 | Feb. 10 - 16 |
Fundamentally, -omics descriptions provide us with lists of components. However, to understand how things work, we need to address the relationships of the components - how things are put together: the molecular blueprints. At its most basic level, this is the question of molecular interactions in the cell. A quantitative description of molecular interactions relies heavily on the mathematical discipline of graph theory. Cytoscape is a visualization and analysis platform for molecular interactions.
|
Quiz 5 | Assignment 6 |
| Feb. 17 - 23 | Reading Week - School closed | |||
| 7 | Feb. 24 - Mar. 2 |
Here we focus on the biological objects of "Interaction Science".
|
Quiz 6, Open Project outline due in class | Assignment 7 |
| S y s t e m s | ||||
| Week | Date | Topics | Activities | Assignment |
| 8 | Mar. 3 - 9 |
Several key networked systems exist in the cell. Here we discuss their paradigms, how they are constructed from experimental data and examples of how they can be organized in databases.
|
Quiz 7 | Assignment 8 |
| 9 | Mar. 10 - 16 |
Obviously, one of the key challenges of computational systems biology is to define systems from -omics scale data. This task is sometimes referred to as "reverse engineering", it employs a multitude of methods; among them information theory has proven to be one of the cornerstones through the quantification of mutual information.
|
Quiz 8 | Assignment 9 |
| 10 | Mar. 17 - 23 |
Life is not static, only death is. Yet, the dynamic nature of biological systems is often overlooked.
|
Quiz 9 | Assignment 10 |
| M o d e l s | ||||
| Week | Date | Theme | Activities | Assignment |
| 11 | Mar. 24 - 30 |
The notion that computational biology will at some time become predictive is tied to the idea that we will be able to model the cell's systems. Many approaches exist, each with its own strengths and weaknesses; how to integrate such models - preferrably across multiple scales - is a question of its own.
|
Open Project implementation due in class | Assignment 11 |
| 12 | Mar. 31 - Apr. 6 |
Do we really understand systems biology? Computational Synthetic Biology is the ultimate test.
|
— | Assignment 12 |
In depth...
Resources
- Course related
- Prerequisites for the course
- The Course Google Group.
- Netiquette for the Group mailing list
- Contents related
- The VMD tutorial
- A Stereo Vision tutorial
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