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, this site is unlikely to be useful. 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 are currently under intense revision to prepare for the 2018 Winter session.
This course has started on Tuesday, January 9. 2018. Our first class meeting is on Tuesday, January 16.
Everyone has now been enrolled on the course mailing list (with their official UofT email address) and should have received a welcome email from me. If you have not received an email from me, contact me - I may not be aware that you are enrolled in this course
Contents
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 2018 course...
In this course we pursue a task in computational systems biology of human genes in project oriented format. This will proceed in three phases:
- First, we will review basic computational skills and bioinformatics knowledge to bring everyone to the same level. In all likelihood you will need to start with these tasks well in advance of the actual lectures. This phase will end with a comprehensive quiz in week 3;
- Next we'll focus on data integration and definition of features. As an example, we will integrate gene expression data from different experiments into a common set of features. Each student will contribute data from one experiment. The results of this phase will be the topic of our first Oral Exam;
- Finally, we will each adopt a biological "system" in human cells and use machine learning methods to attempt to refine its gene membership and assign roles to its member genes. The results will form the basis of our final Oral Exam;
- There are several meta-skills that you will pick up "on the side" these include time management, working according to best practice of reproducible research in a collaborative environment on GitHub; report writing, and keeping a scientific lab journal.
Organization
- Dates
- BCB420/JTB2020 is a Winter Term course.
- Lectures: Tuesdays, 16:00 to 18:00. (Classes start at 10 minutes past the hour.)
- Final 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.
Prerequisites and Preparation
This course has formal prerequisites of BCH441H1 (Bioinformatics) or CSB472H1 (Computational Genomics and Bioinformatics). I have no way of knowing what is being taught in CSB472, and no way of confirming how much you remember from any of your previous courses, like BCH441 or BCB410. Moreover there are many alternative ways to become familiar with important course contents. Thus I generally enforce prerequisites only very weakly and you should not assume at all that having taken any particular combination of courses will have prepared you sufficiently. What I try to do instead is make the contents of the course very explicit. If your preparation is lacking, you will have to expend a very significant amount of effort. This is certainly possible, but whether you will succeed will depend on your motivation and aptitude.
The course requires (i) a solid understanding of molecular biology, (ii) solid, introductory level knowledge of bioinformatics, (iii) a working knowledge of the R programming language.
The prerequisite material for this course covers the contents of the 2017 BCH441 course:
- <command>-Click to open the Bioinformatics Learning Units Map in a new tab, scale for detail.
- Open the Bioinformatics Knowledge Network Map and get an overview of the material. You should confidently be able to execute the tasks in the four Integrator Units .
- If you have taken an earlier version of BCH441 (pre 2017), you will need to work through many of the units, since very much new material has been added.
- If you have taken BCH441 in 2017, most of the material will be familiar. You will need to review some of the units and familiarize yourself more with the R programming aspects.
- If you have not taken BCH441, you will need to work through the material rather carefully.
The preparatory material for BCB420 is linked from the BCB420-specific map below. It covers a subset of the BCH441 material and will be the subject of our first Quiz in the third week of class. We will hold a mock-quiz in the second week.
The "Knowledge Network"
Supporting learning units for this course are organized in a "Knowledge Network" of self-contained units that can be worked on according to students' individual needs and timing. Here is the detailed map. It contains links to all of the units.
- <command>-Click to open the Learning Units Map in a new tab, scale for detail.
- Hover over a learning unit to see its keywords.
- Click on a learning unit to open the associated page.
- The nodes of the learning unit network are colour-coded:
- Live units are green
- Units under development are light green. These are still in progress.
- Stubs (placeholders) are pale. These still need basic contents.
- Milestone units are blue. These collect a number of prerequisites to simplify the network.
- Integrator units are red. These embody the main goals of the course.
- Units that require revision are pale orange.
- Units that have a black border have deliverables that can be submitted for credit. Visit the node for details.
- Arrows point from a prerequisite unit to a unit that builds on its contents.
(Many new units will be added to the map as the course progresses, reload the map frequently.)
Everything starts with the following three units:
This should be the first learning unit you work with, since your Course Journal will be kept on a Wiki, as well as all other deliverables. This unit includes an introduction to authoring Wikitext and the structure of Wikis, in particular how different pages live in separate "Namespaces". The unit also covers the standard markup conventions - "Wikitext markup" - the same conventions that are used on Wikipedia - as well as some extensions that are specific to our Course- and Student Wiki. We also discuss page categories that help keep a Wiki organized, licensing under a Creative Commons Attribution license, and how to add licenses and other page components through template codes.
Keeping a journal is an essential task in a laboratory. To practice keeping a technical journal, you will document your activities as you are working through the material of the course. A significant part of your term grade will be given for this Course Journal. This unit introduces components and best practice for lab- and course journals and includes a wiki-source template to begin your own journal on the Student Wiki.
In paralell with your other work, you will maintain an insights! page on which you collect valuable insights and learning experiences of the course. Through this you ask yourself: what does this material mean - for the field, and for myself.
- Once you have completed these three units, get started immediately on the Introduction-to-R units. You need time and practice, practice, practice[1] to acquire the programming skills you will need for the course.
- Whenever you want to take a break from studying R, get done with the other preparatory units.
At the end of our preparatory phase (after week 2) we will hold a comprehensive, non-trivial quiz on the preparatory units and on R basics.
Grading and Activities
| Activity | Weight BCB410 - (Undergraduates) |
Weight JTB2020 - (Graduates) |
| Self-evaluation and Feedback session on preparatory material("Quiz"[2]) | 20 marks | 20 marks |
| First Oral Exam | 20 marks | 15 marks |
| Second Oral Exam | 30 marks | 25 marks |
| Journal | 25 marks | 25 marks |
| Insights | 5 marks | 5 marks |
| Manuscript Draft | 10 marks | |
| Total | 100 marks | 100 marks |
Marks adjustments
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 them 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. But do keep it honest and carefully consider our rules on Plagiarism and Academic Misconduct.
Timetable and syllabus
Syllabus and activities in progress for the 2018 Winter Term ...
| Week | In class: Tuesday, January 9 | This week |
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| Week | In class: Tuesday, January 16 | This week |
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| Week | In class: Tuesday, January 23 | This week |
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| Week | In class: Tuesday, January 30 | This week |
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| Week | In class: Tuesday, February 6 | This week |
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| Week | In class: Tuesday, February 13 | This week |
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| Week | In class: Tuesday, February 20 | This week |
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| Week | In class: Tuesday, February 27 | This week |
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| Week | In class: Tuesday, March 6 | This week |
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| Week | In class: Tuesday, March 13 | This week |
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| Week | In class: Tuesday, March 20 | This week |
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| Week | In class: Tuesday, March 27 | This week |
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| Week | In class: Tuesday, April 3 | This week |
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Resources
- Course related
- Student Wiki
- The Course Google Group.
- Netiquette for the Group mailing list
| 325C78 | 7097B8 | 9BACCF | A8A5CC | D7C0F0 |
Notes
- ↑ It's practice!
- ↑ I call these activities Quiz sessions for brevity, however they are not quizzes in the usual sense, since they rely on self-evaluation and immediate feedback.
