Coursebooks 2018-2019

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Statistics for genomic data analysis

MATH-474

Lecturer(s) :

Goldstein Darlene

Language:

English

Summary

After a short introduction to basic molecular biology and genomic technologies, this course covers the most useful statistical concepts and methods for the analysis of genomic data.

Content

Keywords

statistics; statistical methods; data analysis; DNA; RNA; mRNA; genomics; genomic data; microarray; sequencing data; NGS; NGS technologies; machine learning; R statistical software; BioConductor

Learning Prerequisites

Important concepts to start the course

Elementary statistics

Previous experience with R is helpful (but not necessary)

 

Learning Outcomes

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

Transversal skills

Teaching methods

Lectures and computer practical exercises

Expected student activities

Regular attendance in class, practical exercises, prepare a short report (max. 10 pages) on an analysis of genomic data using tools and methods from the course

Assessment methods

Evaluation is based on a written report of a genomic data analysis project.

In the programs

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     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German