Computational Systems Biology: Sequences, Structures, and Networks

Computational Systems Biology:

Sequences, Structures, and Networks

Type:   Lecture
Ects: 4.0  (to be approved)
Lecturer:  Dr. Arthur Dong, Dr. Shaila Roessle
Time:    Thursday, 10:30 - 12:00
Language:  English
Room:  MI 01.09.034



Traditional molecular biology follows the reductionist paradigm of "one gene, one protein, one function". However, with the ever increasing amount of data generated through genome-scale experiments, it becomes clear that "the whole is more than the sum of the parts".

In this lecture, we introduce the exciting new field of computational systems biology, which attempts to integrates orthogonal data to understand biological systems as a whole. The lecture can be divided into three parts.

In part one, we overview the field and present the big picture and motivation. A primer of molecular biology is included to make sure that all course participants, especially those with purely computer science background, have the requisite vocabulary. To conclude, we show how traditional sequence analysis can play a role in systems biology.

Part two focuses on protein structure. While systems biology itself looks at the big picture, for a complete understanding one still has to go down to the individual building blocks. "Parts" and "whole" are really the two sides of the same coin. With the facility to freely navigate between the two, one will understand both at a deeper level.

Part three is "proper" network-based systems biology. The prime focus is protein-protein interaction networks, but others such as gene-regulatory and metabolic networks are also presented. While we provide the necessary theoretical background on networks, the focus is on addressing significant biological questions and conducting cutting-edge research. Finally, we introduce pathogen-host interactions as a first example of integrating multiple systems.

The course is aimed at Master students, but should be accessible to Bachelor students as well. 

Topics and Readings

Lecture 1: Overview and Motivation

Lecture 2: Review I

Lecture 3: Review II

Lecture 4Protein structures and intrinsic disorders in complete genomes



Lecture 5: From regular graphs to complex networks


  • Collective dynamics of 'small-world' networks. Nature 393, 440-442 (4 June 1998)
  • Emergence of Scaling in Random Networks. Science 15 October 1999: Vol. 286. no. 5439, pp. 509 - 512


Lecture 6: Further properties of complex (biological) networks


  • Error and attack tolerance of complex networks. Nature 406, 378-382 (27 July 2000)
  • Lethality and centrality in protein networks. Nature 411, 41-42 (3 May 2001)
  • Specificity and Stability in Topology of Protein Networks. Science 3 May 2002: Vol. 296 no. 5569 pp. 910-913


Lecture 7: Protein Engineering I (Marc Offman)

Lecture 8: Protein Engineering II (Marc Offman)

Lecture 9: Hierarchical Networks and Network Motifs


  • Hierarchical Organization of Modularity in Metabolic Networks. Science 30 August 2002: Vol. 297 no. 5586 pp. 1551-1555
  • Network Motifs: Simple Building Blocks of Complex Networks. Science 2002 Oct 25;298(5594):824-7



Lecture 10: Systems Pharmacology (Andrea Schafferhans)

Lecture Slides WS 2010/2011


Lecture 1 (10-21-2010)

3.8 M


Lecture 2 (10-28-2010)

1.2 M


Lecture 3 (11-04-2010)

4.7 M


Lecture 4 (11-11-2010)

1.6 M


Lecture 5 (11-18-2010)

0.9 M


Lecture 6 (11-25-2010)

599 K


Lecture 7+8 (12-09-2010, 12-16-2010)

13.3 M


Lecture 9 (01-13-2011)

409 K


Lecture 10 (01-20-2011)

3.8 M

Lecture Videos WS 2010/2011


Lecture 1 (10-21-2010)

356 M


Lecture 2 (10-28-2010)

372 M


Lecture 3 (11-04-2010)

119 M


Lecture 5 (11-18-2010)

275 M


Lecture 6 (11-25-2010)

396 M


Lecture 7 (12-09-2010)

316 M


Lecture 8 (12-16-2010)

283 M


Lecture 9 (01-13-2011)

482 M


Lecture 10 (01-20-2011)

390 M