Course Description 

After a review of the basic mechanisms of gene regulation and signaling, this course will expose students to several technological and methodological tools for systematically dissecting regulatory networks and systems. Emphasis is on extracting global insight from genome-scale molecular biology datasets. Students will participate in class discussions of research papers, solve systems biology problems using the R statistical software and write an independent paper. 

Syllabus

Introduction to regulatory networks and systems biology 

  1. Overview of the course and introduction to genome-scale data 
  1. Mechanisms of gene regulation 
  1. Systems theory: cells as circuits 
  1. High-throughput molecular biology for complex systems 

Visualization and analysis of high-dimensional data in R 

  1. Finding and downloading data 
  1. Discovering gene expression patterns 
  1. Dimensionality reduction and comparison of genome-scale datasets 
  1. Simple statistical tools to analyze regulatory networks 

Transcription factors and their binding sites 

  1. Finding binding sites and motif matrices using high-throughput experiments 
  1. Prediction of binding sites in DNA sequences with motif matrices 
  1. Predicting gene expression using transcription factor binding sites 
  1. Combinatorial logic and the cis-regulatory code 

Signaling pathways and regulatory networks 

  1. Inferring regulatory networks from gene deletion experiments 
  1. Protein complexes and co-regulation of interacting proteins 
  1. Phosphoproteomics  
  1. Subcellular localization of proteins and mRNAs 

Prerequisite 

BCH311H1 / CSB349H1 / MGY311Y1 

Lecturer(s) 

Prof. A. Moses
alan.moses@utoronto.ca 

Contact Hours 

24L 

Evaluation (Subject to change) 

Data analysis problems in R
Independent paper
Participation
Attendance 

 

 

 

Last updated on June 13th, 2022