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  • CSE 591 (Fall 2008)
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CSE 591 - Analysis of biomolecular networks and their components

Jörg Hakenberg

Office: BYENG 569/572

Lectures: Tu & Th, 4:30-5:45pm, Artisn Crt Brckyrd 190

Course catalog: #88741

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Summary

This course offers an introduction to understanding and analyzing biomocular networks and their components. We will start with an overview of relevant biochemical concepts (components such as genes and proteins; types of interactions and types of biological networks). We will then discuss the graph theoretic foundations necessary to network analysis, and have look at global network properties. After presenting some examplary networks and how they can be stored and visualized, we want to discuss recent work on the topic of network analysis.

Grading is based on a mid-term and final exam (25% each), a class project (30%), and a presentation at the end of the course (20%).


Topics

  • Molecular Biology 1 (biochemistry, gene, protein, genotype, phenotype, biological processes, protein interactions, signal transduction, gene regulation, ..)
  • Molecular Biology 2 (interaction detection methods, microarray, mRNA, miRNA, ..)
  • Pharmacogenetics, -genomics, -kinetics, and -dynamics (drug metabolism, drug targets, The Druggable Genome, ..)
  • Bioinformatics (alignment, ..)
  • Information extraction from text (text mining, relation mining)
  • Graph Theory (directionality, hypergraphs, adjacency matrices, graph traversal, ..)
  • Network properties (scale free, random graph, power law, distance, small world, modulatiry, subgraphs)
  • Network models (Erdös-Renyi, Watts-Strogatz, Barabasi-Albert)
  • Network centralities (centrality, degree, shortest paths, closeness, betweenness, eccentricity, PageRank, HITS, ..)
  • Network motifs (feed-forward loop, ..)
  • Notations and markup languages (Kohn interaction maps; BioPAX, SMBL, GPML)
  • Network and pathway visualization, browsing (tools: Cytoscape plugins, AliBaba, ..)
  • Data sources (KEGG, BioPAX, interaction maps, ..)
  • Biological networks (signal transduction, gene regulation, protein interaction, metabolic pathways)
  • Selected, recent papers on biological network analysis

Tentative schedule

  1. 8/27 -- Introduction
  2. 9/01 -- Genes and proteins
  3. 9/03 -- Biological processes
  4. 9/08 -- Genotype and phenotype
  5. 9/10 -- Reconstructing metabolic pathways (Shanshan Liang)
  6. 9/15 -- Graph theory
  7. 9/17 -- Global network properties
  8. 9/22 -- Network centralities
  9. 9/24 -- Class projects
  10. 9/29 -- Network models
  11. 10/1 -- Statistical testing; network motifs
  12. 10/6 -- PTQL (Shanshan Liang)
  13. 10/08 -- Mid-term summary
  14. 10/13 -- Mid-term exam
  15. 10/15 -- Network clustering
  16. 10/20 -- Notations, markup languages
  17. 10/22 -- Structure and function of the feed-forward loop motif
  18. 10/27 -- Protein interaction detection methods
  19. 10/29 -- Recent studies: "Human proteins interacting with pathogens"
  20. 11/03 -- "Finding local communities in protein networks"
  21. 11/05 -- "Automated pathway building in biological association networks" (Shanshan Liang / Chitta Baral)
  22. 11/10 -- Student presentations: class projects; 3 slides each
  23. 11/12 -- "Clustering to find functional modules and predict function -- when and how?"
  24. 11/17 -- "Quantitative modeling and analysis of genetic regulatory networks"
  25. 11/19 -- Petri nets & extensions
  26. 11/24 -- all student presentations moved to 12/03 => 2h, no class today
  27. 12/01 -- Summary
  28. 12/03 -- Student presentations: class projects; 10-15 min. each, 10 slides; starts at 4 p.m.!
  29. 12/08 -- Final exam

Thursday, Nov 26: Thanksgiving (observed). Depending on how many students are involved in the project meeting on Nov 19, there might be no class on this day.


Course material

There are some books I recommend for further reading. However, most deal with a specific topic only (covered on one or two days) or become useful only if you plan on working in this field (project, thesis, ...). I will bring all books into the class on the first day, so everybody can have a look at them. Most of the topics have nice Wikipedia entries, however, and you can start reading from there.

Books:
  • Analysis of Biological Networks, Junker and Schreiber (editors), Wiley and Sons, ISBN 978-0470041444 (2008).
    view at Amazon, $60-75.
  • Systems Biology: Properties of Reconstructed Networks, by B.O. Palsson, CUP ISBN 978-0521859035 (2006).
    view at Amazon, $32-60.
  • http://www.amazon.com/Reverse-Engineering-Biological-Networks-Opportunities/dp/157331689X
  • http://www.amazon.com/gp/product/1934115029/
  • http://www.amazon.com/Biochemical-Pathways-Biochemistry-Molecular-Biology/dp/0471331309
Glossary and online resources:
  • Graph theory - an intro to graph theory, electronic edition of the book by R. Diestel, 3rd edition, Springer, 2005.
  • Barabasi-Albert model (Wikipedia) - generating random scale-free networks
  • Erdös-Renyi model (Wikipedia) - models for generating random graphs
  • Kohn interaction maps: MIM
    Paper: Molecular Interaction Map of the Mammalian Cell Cycle ..., MBC 10(8):2703-2734, 1999.
  • Pharmacogenetics (Wikipedia)
  • Pharmacogenomics (Wikipedia)
  • Watts and Strogatz model (Wikipedia) - produces graphs with small-world properties