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A. Among other things, I can use the NetworkAnalyzer to identify important hub

proteins, i.e. strongly networked nodes.

B. The NetworkAnalyzer identifies an “average number of neighbors” of less than 1.

C. The NetworkAnalyzer identifies an “average number of neighbors” of more than 3.

D. Looking at the Node Degree Distribution plot, I see five nodes with three interac­

tions and ten nodes with five interactions.

E. Looking at the Node Degree Distribution plot, I see one node with five interac­

tions – this represents a hub node given the average number of neighbors parameter.

Mathematical modeling of regulatory networks:

Task 5.12

Name and describe software for mathematical modeling of biological networks.

Task 5.13

Describe three different approaches to mathematical modeling of biological networks

(Boolean, quantitative, and semiquantitative).

Task 5.14

State advantages and disadvantages of mathematical modeling of biological networks.

Task 5.15

Describe how one would bioinformatically model a biological network, e.g., the cAMP

pathway (briefly describe: what data, what steps, what possible software).

Task 5.16

Which statements about the mathematical modeling of regulatory networks are correct

(multiple answers possible)?

A. Boolean, quantitative, and semiquantitative modeling are three mathematical mod­

eling methods.

B. Boolean modeling always considers the on/off (0/1) state of a system.

C. Quantitative modeling is not able to consider the system state in the interval

between 0 and 1 and thus cannot model kinetic data, e.g. via Michaelis-Menten

kinetics.

D. Semiquantitative modeling is a combination of Boolean and quantitative modeling,

where I do not necessarily need information about kinetics.

Task 5.17

What is meant by a “steady state” condition of a network?

5.3  Exercises for Chap. 5