BIO-369 / 4 credits

Teacher: Bitbol Anne-Florence Raphaëlle

Language: English


Summary

Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way.

Content

Keywords

Biological data, data science, sequencing data, neuroscience, population genetics, random variable, random walk, information theory, statistical physics, entropy, mutual information, inference, dimensionality reduction.

Learning Prerequisites

Required courses

Analysis; probability and statistics; linear algebra; general physics; programming.

Recommended courses

Introductory machine learning.

Learning Outcomes

By the end of the course, the student must be able to:

  • Manipulate notions of statistics, information theory and statistical physics.
  • Apply these notions to biological data.
  • Analyze biological data in a quantitative way.
  • Perform data analysis in Python.

Teaching methods

Lectures, exercises, programming labs.

Assessment methods

Written final exam during the exam session, graded numerical mini-project.

Resources

Bibliography

Reference textbooks:

  • P. Nelson, Physical Modeling of Living Systems, WH Freeman, 2014
  • D. MacKay, Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003

More advanced textbooks:

  • W. Bialek, Biophysics: Searching for Principles, Princeton University Press, 2012
  • T. Cover and J. Thomas, Elements of Information Theory, 2nd ed, Wiley Interscience, 2006

In the programs

  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Randomness and information in biological data
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Randomness and information in biological data
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Randomness and information in biological data
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22