Staff

Luay K. Nakhleh

Instructor

nakhleh@rice.edu

Office Hours
by appointment, DH 3119

Nikola Ristic

Teaching Assistant

nr10@rice.edu

Office Hours
by appointment, DH 3117

Course Information

  • MEETING TIME AND PLACE: Tuesday and Thursday, 1:00-2:15; Keck Hall (KCK) 101.
  • TEXTBOOK: The course will not adhere to any textbook, but the following texts are highly recommended and cover different aspects of networks:
    • A First Course in Systems Biology, by E. Voit. Garland Science, 2012.
    • Systems Biology: A Textbook, by E. Klipp et al. Wiley-Blackwell, 2009.
    • Principles of Computational Cell Biology, by V. Helms. Wiley-Blackwell, 2008.
    • Networks: An Introduction, by M.E.J. Newman. Oxford University Press, 2010.
    • Computational Modeling of Gene Regulatory Networks – A Primer, by H. Bolouri. Imperial College Press, 2008.
    • An Introduction to Systems Biology, by U. Alon. Chapman & Hall/CRC, 2006.
    • Biological Networks, edited by F. Kepes. World Scientific, 2007.
  • INTENDED AUDIENCE: This is a course about mathematical modeling and computational analysis of networks that arise in biological applications. As such, the course requires knowledge in math (mainly Algebra, and occasionally differential equations) and computer science (algorithms, graph theory,…). Familiarity with programming will also be assumed.
  • TOPICS TO BE COVERED: Tentatively, we will cover the following topics (in the given order).
    1. Networks in biology.
    2. Graph-theoretic modeling and analysis of networks.
    3. Discrete dynamic modeling (Boolean networks, Petri nets, etc.).
    4. Continuous dynamic modeling (ODEs, stochastic simulation,..).
    5. Probabilistic modeling (Probabilistic Boolean networks, Bayesian networks, etc.).
    6. Network inference from experimental data.
    7. Genome-scale modeling and network integration.
    8. Evolution of molecular networks.
    9. Networks as tools (network-guided GWAS studies, FBA and epistasis detection, protein function prediction, epidemic spreading, etc.).
  • GRADING:
    • Homework assignments: 50% (done individually).
    • Midterm exam on October 8, 2013 (in-class; only one A4 sheet of notes is allowed): 25%.
    • Midterm exam on November 26, 2013 (in-class; only one A4 sheet of notes is allowed): 25%.
  • STUDENTS WITH DISABILITY: Any student with a documented disability needing academic adjustments or accommodations is requested to speak with me during the first two weeks of class. All discussions will remain confidential. Students with disabilities will need to also contact Disability Support Services.
  • HONOR CODE: The Honor Code of Rice University applies. In particular, the solutions to homework and exam problems submitted by a student must be the work of that student and written in that student’s own words.

Course Material

 

Slides Set # Topic Slides Additional material
1 Networks in biology PDF Syllabus
2 Molecular cell biology: A review PDF  
3 Modeling in biology PDF  
4 Graph-theoretic properties PDF Newman
2003
5 Graph-theoretic properties of biological networks PDF Barabasi & Oltvai 2004,
Albert 2005,
Przulj et al. 2004
6 Discrete dynamic modeling: Boolean networks and Petri
nets
PDF Liang et al., 1998,
Heiner et al., 2008
7 Reaction kinetics PDF  
8 Enzyme kinetics PDF  
9 Kinetics of gene regulation PDF Kuznetsov
et al., 2004
10 Kinetics of regulatory networks: Basic building
blocks
PDF Tyson
et al., 2003
11 Analyses of biological systems models PDF  
12 Probabilistic modeling: Bayesian networks PDF Needham et al., 2007
13 Analyzing stoichiometric matrices PDF Papin and Palsson,
2004
14 Flux-balance analysis (FBA) and metabolic control
analysis (MCA)
PDF  
15 Model fitting PDF  
16 Network motifs PDF  
17 Evolution of genes and genomes PDF  
18 Comparative network analysis PDF  
19 Networks as a guiding tool PDF