Biological Dynamics & Networks CHE 559 / PHY 559 / AMS 537

Spring Tu/Th 2:30-3:50 PM in Laufer Center 101

Tom MacCarthy, Course PI

Guest lecturers: Ken Dill, TBA

This course will provide a solid foundation in key theoretical concepts for the study of dynamics in biological systems and networks at different scales ranging from the molecular level to metabolic and gene regulatory networks.

 

Reference Books

  • Ken Dill, Molecular Driving Forces: Statistical Thermodynamics in Biology, Chemistry, Physics, and Nanoscience
  • Bernhard Palsson, Systems Biology: simulation of dynamic network states
  • Eberhard Voit, A first course in Systems Biology
  • Uri Alon, An introduction to Systems Biology
  • M.E.J. Newman, Networks: an introduction

 

Topics Speakers
Introduction to networks and statistical thermodynamics
  1. Brief introduction to networks in biology and beyond
  2. Physical kinetics
  3. Diffusion, Smoluchowski
  4. Random flights
 MacCarthy, Dill
Statistical thermodynamics II
  1. Waiting times
  2. Brownian ratchets
  3. Chemical kinetics
  4. Transition states
 Dill
Biochemical networks
  1. Rate laws and basic properties of reactions
  2. Reversible linear and bilinear reactions
  3. Connected reversible linear and bilinear reactions
  4. Autocatalysis and dynamical stability

Reference: Palsson, Chapters 2 and 4

 MacCarthy
Enzyme kinetics
  1. Background on enzyme catalysis
  2. Michaelis-Menten kinetics
  3. Hill kinetics for enzyme regulation
  4. Cooperative phenomena

Reference: Palsson, Chapter 5

 MacCarthy
Network measurements
  1. Networks as graphs
  2. Non-biological networks: technological, social and information networks
  3. Degree distribution
  4. Centrality measures

Reference: Newman, Chapters 6,7

 MacCarthy
Large-scale structure of networks
  1. The small-world effect
  2. Power laws and scale-free networks
  3. Clustering coefficients

Reference: Newman chapter 8

 TBA
Network evolution models
  1. Properties of random graphs
  2. Preferential attachment models

Reference: Newman chapters 12,14

 TBA
Metabolic networks I
  1. Background on metabolism
  2. Modeling large systems using stoichiometric networks
  3. Case study: glycolysis

Reference: Palsson, Chapters 7 and 10

 MacCarthy
Metabolic networks II
  1. Metabolomics
  2. Metabolic network reconstruction
  3. Flux analysis

Reference: Voit, Chapters 3 and 8

 MacCarthy
Gene regulatory networks I
  1. Background on gene regulation and transcription networks
  2. Network motifs
  3. Biological oscillators and autoregulation

Reference: Alon, Chapters 2-4

 MacCarthy
Signal transduction systems
  1. Background on signal transduction
  2. Two-component signaling systems
  3. Bistability and hysteresis

Reference: Voit, Chapter 9

 MacCarthy
Robustness
  1. Overview of biological robustness
  2. Robustness in signalling networks: bacterial chemotaxis
  3. Robust patterning in development

Reference: Alon, Chapters 7,8

 MacCarthy
Algorithms for network analysis
  1. Modularity in biology
  2. Community detection

Reference: Newman, Chapter 11

 MacCarthy
Modeling noise
  1. Definitions of intrinsic and extrinsic noise
  2. Case study: M.B. Elowitz et al., 2002, Stochastic gene expression in a single cell, Science, 297, 1183-1186.
  3. Gillespie algorithm
 TBA