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 and computational systems biology, which have a broad impact on the understanding of gene regulation processes and biological systems mechanisms.

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.

Teaching Staff:


  • Tuesday & Thursday, 10:05am to 11:25pm.
  • Hybrid participation. Zoom (remote) and Stewart Biology Building S3-3 (in-person).

Office hours:

Prof. Jérôme WaldispühlTuesday after classENGTR 3106
Roman Sarrazin-GendronTBDOnline

Course Webpage:

Course Material:
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:

  • [CB2000] Peter Clote and Rolf Backofen, Computational Molecular Biology: An Introduction, Wiley, 2000.
  • [DEKM1998] Richard Durbin, Sean R. Eddy, Anders Krogh, and Graeme Mitchison, Biological Sequence Analysis, Cambridge University Press, 1998.
  • [GR2014] Jan Gorodkin and Walter Russo, RNA Sequence, Structure, and Function: Computational and Bioinformatics Methods, Humana Press, 2014.
Lecture slides will be made available in PDF form on the course web page.

Your final grade will be calculated as follows:

  • 45% for 3 assignments (15% each)
  • 40% for the final exam
  • 15% for a paper review
The final exam is closed book and electronic devices are not allowed.


Release DateDue DateAnnounce
April 18, 2022April 26, 2022We released a practice exam to help you preparing the final exam.
March 27, 2022April 12, 2022The third assignment is now available!.
Mar 24, 2022Mar 31, 2021Guidelines for the student presentations: The format is free. Though, we encourage you to follow the following guidelines. The total time allocated for the presentation if approximately 20 minutes (15 minute talk + 5 min of questions) for single presenters and 30min (20 minute talk + 10 min of questions) for groups of two. This means that your slide deck should most likely not include more than 15 slides. The presentation should clearly explain (i) the objectives, (ii) context and previous contributions, (iii) Methodology, (iv) validation of the methods and (v) discussion and future directions. In particular, it is important to clearly describe the methodological contribution. You do not need to go into the technical details but you should highlight the key principles and be ready to answer questions about it.
Please, send a PDF of your slides to the instructor before the beginning of the class.
Feb 28, 2022Mar 11, 2022The second assignment is now available!.
Feb 21, 2022March 8, 2022Instructions for the paper review assignment are available in the first slides of Lecture 14.
Jan 28, 2022Feb 15, 2022The first assignment is now available!.
Jan 6, 2022Welcome to COMP564!


Lecture 1Jan 6Syllabus. Introduction to RNA. Timeline of RNA bioinformatics.[Slides]
Lecture 2Jan 11Introduction to RNA structure and modeling[Slides]
Chapter 2 of [GR2014]
Lecture 3Jan 13RNA secondary structure prediction[Slides]
Chapter 4 of [GR2014]
Lecture 4Jan 18Minimum free energy and partition function with the Nearest neighbor energy model[Slides]
Chapter 4 of [GR2014]
Lecture 5Jan 20Stochastic prediction of RNA secondary structures
Application: The Vienna RNA package (RNAsubopt).
Chapter 4 of [GR2014]
Lecture 6Jan 24Comparative modeling of RNAs.
Application: Infernal & the Rfam database.
Chapter 3 of [GR2014]
Lecture 7Jan 27Simultaneous folding and alignment of structured RNAs.[Slides]
Chapter 5, 8, and 9 of [GR2014]. Chapter 6, 9, and 10 of [DEKM1998].
Lecture 8Feb 1RNA sequence-structure maps and simulation the evolution of RNA populations
Application: Jupyter notebook for simulating RNA evolution.
Chapter 16 of [GR2014]
Lecture 9Feb 3Pseudo-knots and RNA-RNA interaction predictions[Slides]
Chapter 19 of [GR2014]
Lecture 10Feb 8Guest lecture by Francois Major: RNA functional structures are made of theoretically predicted overrepresented blocks
Lecture 11Feb 10RNA 3D Modeling[Slides]
Chapter 13 of [GR2014]
Lecture 12Feb 15RNA 3D structure prediction[Slides]
Lecture 13Feb 17Introduction to Protein structure
Application: The protein data bank (PDB)
Lecture 14Feb 22Protein secondary structure prediction using Neural Networks[Slides]
Lecture 15Feb 24Protein residue contact prediction[Slides]
Lecture 16Mar 8Protein fold recognition and threading[Slides]
Lecture 17Mar 10Molecular dynamics simulation[Slides]
[MD Tutorial] [GROMACS5 Tutorial] [Data]
Lecture 18Mar 15Protein 3D structure prediction[Slides]
Lecture 19Mar 17Guest lecture by Vincent Mallet: Structural bioinformatics and machine learning for drug design[Slides]
Lecture 20Mar 22Minimalist models: Protein folding on HP lattice models[Slides]
Lecture 21Mar 243D Genomics[Slides]
Lecture 22Mar 29Analysis and alignment of Protein-Protein Interaction networks[Slides]
Lecture 23Mar 31Student presentations
Lecture 24Apr 5Student presentations
Lecture 25Apr 7Student presentations
Lecture 26Apr 12Special Topics
Note: This schedule is subject to modification.


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 policies
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:

Jérôme Waldispühl
3630 University Street, Room 3106, Montreal QC H3A 0C6
(Phone) +1 514 398 5018

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