An introduction to computational structural and systems biology. Theory and practice of Protein and RNA structure prediction, RNA-RNA, Protein-RNA, protein-protein interaction prediction, biological network analysis.
This class extends the material covered in COMP462/561 (i.e. Computational Biology Methods and Research). We introduce fundamental concepts and techniques in computational structural biology
This course covers the theory and practice of computational techniques used in these research areas, such as dynamic programming algorithms for RNA structure analysis, molecular dynamics and machine learning techniques for protein structure prediction, and graphical models for biological networks analysis. We also feature practical sessions introducing how to use state-of-the-art software.
|Prof. Jérôme Waldispühl||Tuesday after class||ENGTR 3106|
|Roman Sarrazin-Gendron||Thursday 2pm-3:30pm||ENGTR 3110 (if no one knock at 3140)|
Course Webpage: http://www.cs.mcgill.ca/~jeromew/comp564.html
All the material needed for this class will be available on the public course web page. There is no required textbook. Although, we recommend the following textbooks to deepen the material presented in class:
Your final grade will be calculated as follows:
|Release Date||Due Date||Announce|
|Mar 12, 2019||Apr 12, 2019||A draft of second assignment is now available online. Please, note that a final version will be posted soon.|
|Mar 11, 2019||At least 24h before your presentation||You will use a pptx template for the oral presentation of your paper review. Instruction on the content of the slidedeck and guideline for your presentation are included in the comments of the slides. You are not allowed to change the number of slides. It is your responsability to identify the important aspects of the paper that have to be highlighted in your presentation.|
|Feb 25, 2019||The paper review assignment is now available online.|
|Feb 6, 2019||Mar 4, 2019||The first assignment is now available online.|
Note on Q3 (26/02/2019): The threshold used in Q3 is correct. Although the number of samples required to reach this value might be larger than the values suggested for testing in the assignment (i.e. >10,000). In the formula of error, you should consider only base pairs found in the dot.ps file. Be careful when converting the values from the dot.ps file.
|Feb 6, 2019||Feb 21, 2019||A selection of papers to review is now available online. Enter your bid in the online form (at least 6) before Feb 21.|
|Feb 5, 2019||We hold a lab session to practice the algorithms covered in class. The class is moved to TR 3120.|
|Jan 7, 2019||Welcome to COMP564!|
|Lecture 1||Jan 8||Syllabus. Introduction to RNA structure and function. Timeline of RNA bioinformatics.||[Slides]|
|Lecture 2||Jan 10 & 15||RNA minimum free energy secondary structure prediction.|
Application: The Vienna RNA package (RNAfold).
Chapter 2 of [GR2014]
|Lecture 3||Jan 17||Ensemble of structures and base pair probabilities.||[Slides]|
Chapter 4 of [GR2014]
|Lecture 4||Jan 22||Stochastic prediction of RNA Secondary Structures.|
Application: The Vienna RNA package (RNAsubopt).
Chapter 4 of [GR2014]
|Lecture 5||Jan 24||Comparative modeling of RNAs.|
Application: Infernal & the Rfam database.
Chapter 3 of [GR2014]
|Lecture 6||Jan 29||Simultaneous folding and alignment of structured RNAs.||[Slides]|
Chapter 5, 8, and 9 of [GR2014]. Chapter 6, 9, and 10 of [DEKM1998].
|Lecture 7||Jan 31||Variations on RNA secondary structure prediction|
Application: The Vienna RNA package (kinefold).
Chapter 13 of [GR2014]
|Lecture 8||Feb 5||Practical session I (TR3120)||[Instructions]|
|Lecture 9||Feb 7||Evolution of RNAs and sequence-structure maps|
Application: Jupyter notebook for simulating RNA evolution.
Chapter 16 of [GR2014]
|Lecture 10||Feb 12||RNA 3D Modeling|
Application: RNA-MoIP and MC-Sym
Chapter 13 of [GR2014]
|Lecture 11||Feb 14||Pseudo-knots and RNA-RNA interaction predictions|
Application: The Vienna RNA package (RNAup).
Chapter 19 of [GR2014]
|Lecture 12||Feb 19||Introduction to Protein structure. Timeline of protein structure prediction.|
Application: The protein data bank (PDB)
|Lecture 13||Feb 21||Protein secondary structure prediction using Neural Networks (Part I)|
|Lecture 14||Feb 26||Protein secondary structure prediction using Neural Networks (Part II)||(Slides from previous lecture)|
|Lecture 15||Feb 28||Protein residue contact prediction|
|Lecture 16||Mar 12||Protein fold recognition and threading|
|Lecture 17||Mar 14||Minimalist models: The HP lattice model|
Application: The CPSP software suite
|Lecture 18||Mar 19||Molecular dynamics simulation|
[Tutorial] [Tutorial 2] [Data]
|Lecture 19||Mar 21||Protein-Protein Interaction network alignment|
Application: Struct2net, IsoRank
|Lecture 20||Mar 26||Practical session II (TR3120)||[Instructions]|
|Lecture 22||Mar 28||Student presentations:
|Lecture 23||Apr 2||Student presentations|
|Lecture 24||Apr 4||Student presentations|
|Lecture 25||Apr 9||Student presentations|
|Lecture 26||Apr 11||Student presentations|
Background & Pre-requisites
Good understanding of basic algorithms (equivalent to COMP251), and core molecular biology concepts (i.e. DNA, RNA, Proteins structure and function). A basic progamming in Python. COMP462/561.
Undergraduate students: You can register to this class with the permission of the instructor.
Policy on discussion Board
Please follow common sense rules and etiquette for discussion board postings: be polite, avoid texting shorthand ("ur" instead of "you are", ...), choose a suitable subject line for your posting and use multiple postings for multiple subjects, keep your postings brief, etc.
Policy on collaborations
We greatly encourage you to discuss the assignment problems with each other. However, these discussions should not go so far that you are sharing code or giving away the answer. A rule of thumb is that your discussions should considered public in the sense that anything you share with a friend should be sharable with any student in the class. We ask you to indicate on your assignments the names of the persons with who you collaborated or discussed your assignments (including TA’s and instructors).
Policy on re-grading
If you wish us to re-grade a question on an exam (or assignment), we will do so. However, to avoid grade ratcheting, we reserve us the right to re-grade other questions on your exam as well.
Policy on final grades
I will use the same rules and formula for calculating the final grade for everyone. We understand that your performances may be influenced by many factors, possibly out of your control. However, that is the only way we can be fair. The only exceptions will be medical exceptions. In that case, I will require a medical note, which has to be also reported to McGill, and to be informed as early as possible. Failure to comply to these rules, may results in the impossibility to invoke a medical exception.
Policy on Assignments
Due date/time, location/mode for returning your solutions, and accepted formats will be announced in class and indicated on the course web page.
Failure to return your assignment in time will results in penalties or even absence of grading. Late submission of 24h or less will receive a penalty of 20%. In all other cases, your assignment will be refused and not graded.
Importantly, solutions that do not follow the requested format will receive a penalty. By default, we only accept PDF or TEXT files. Images (if any) must be embedded in a PDF. Do not compress your files. All files must open on LINUX SOCS workstations.
The quality of the presentation of your solution is very important. Unreadable material, cryptic notations, or bad organization of the material will results in penalties, and potentialy even an absence of grading. If you scan your hand-written solutions, it is your responsability to ensure that you submit a high-quality image (i.e. excellent luminosity, contrast, focus and resolution). The clarity of your explanations will also be an integral part of your final grade.
Policy on programming code
Questions in assignments may require you to write a Python program. We will provide, as much as possible, input and output data to test your programs. However, it will be your duty to ensure that your Java files compile on LINUX SOCS workstations. We will not grade programs that do not compile on these machines.
Submission of class files (instead of Java source files) will be considered as an absence of submission. Do not compress your files.
Use of French in assignments and exams
In accordance with McGill University’s Charter of Students’ Rights, students in this course have the right to submit in English or in French any written work that is to be graded.
McGill University values academic integrity. Therefore, all students must understand the meaning and consequences of cheating, plagiarism and other academic offenses under the Code of Student Conduct and Disciplinary Procedures. See this link for more information.
If you have any additional question, you can contact the instructor:
3630 University Street, Room 3106, Montreal QC H3A 0C6
(Phone) +1 514 398 5018