*BSc and MSc students are co-supervised with Prof. Mathieu Blanchette


Students


Pouriya Alikhani Seara Chen
Pouriya Alikhani 
BSc, McGill University
2017
Focus: machine learning,
C. elegans
Seara Chen 
BSc, McGill University
2016 - 2018
Focus: statistical modeling, 5C/Hi-C
Jack Guo Julie Prost
Jack Guo 
MSc, McGill University
2017 - 2018
Focus: machine learning,
Hi-C
Julie Prost 
MSc, McGill University
2018 - 2019
Focus: machine learning, genome organization
Côme Weber
Côme Weber 
MSc, École Polytechnique
2016
Focus: machine learning,
Hi-C

Courses


COMP 364 Fall 2017:
Computer Tools for Life Sciences (3 Credits)

School of Computer Science, McGill University
Co-instructed with Carlos G Oliver

description

Introduction to computer programming in a high level language: variables, expressions, types, functions, conditionals, loops, objects and classes. Introduction to algorithms, data structures (lists, strings), modular software design, libraries, file input/output, debugging. Emphasis on applications in the life sciences.

By the end of this course, students will be able to:

  1. Design and describe precise, unambiguous instructions that can be used [by a computer] to solve a problem or perform a task
  2. Translate these instructions into a language that a computer can understand (Python);
  3. Write programs that solve complex problems (especially those arising in Life Sciences) by decomposing them into simpler subproblems
  4. Apply programming-style and structure conventions to make your programs easy to understand, debug and modify
  5. Learn independently about new programming-language features and libraries by reading documentation and by experimenting

Python v3.6 (via Anaconda) and Sublime (or any other plain text editor)

textbook

How to Think Like a Computer Scientist: Interactive Edition (Python)

student evaluation

      Quizzes: 5% (10 quizzes worth 0.5% each)
      Assignments: 35% (5 assignments worth 7% each)
      Midterm exam: 20%
      Final exam: 45%

Example lecture below:


An example Jupyter notebook assignment may be downloaded here.
(requires Anaconda and Python 3)