1. Nodes Links Interaction A B Network Proteins Physical Interaction Protein-Protein A B Protein Interaction Metabolites Enzymatic conversion Protein-Metabolite A B Metabolic Transcription factor Target genes Transcriptional Interaction Protein-DNA A B Transcriptional Different types of Biological Networks

2. Finding Local properties of Biological Networks: Motifs Network motifs are recurrent circuit elements. We can study a network by looking at its parts (or motifs) How many motifs are in the network?

3. Finding Local properties of Biological Networks: Motifs

7. What are these motifs? What biological relevance they have? Finding Local properties of Biological Networks: Motifs

8. Autoregulatory loop The probability of having autoregulatory loops in a random network is ~ 0 !!!!. Transcription networks: The regulation of a gene by its own product. Protein-Protein interaction network: dimerization

9. Autoregulatory loop Positive autoregulation Fast time-rise of protein level Negative autoregulation Stable steady state time [protein] time [protein] What is the effect of Autoregulatory loops on gene expression levels?

10. Three-node loops There are 13 possible structures with 3 nodes Feed forward loop XY Z Feedback loop XY Z But in biological networks you can find only 2!

11. Feed Forward loops

12. Coherent Feed Forward Loop in flagella biosynthesis A transcription coherent FFL motif ensures That flagella is synthesized only under appropriate conditions

13. Incoherent Feed Forward Loop in sporulation A transcription incoherent FFL motif produces transient gene expression

14. Feed Back Loops in circadian expression Feed back loops can produce oscillation in gene expression XY Z The Drosophila CWO gene Kadener 2007, Genes and Dev.

15. Single Input Module (SIMs) The SIMs are common in sensory transcription networks: Genes from a same Pathway (Arginine synthesis). Genes responding to stress (DNA repair). Genes that assemble a same biological machine (ribosomal genes).

16. Single Input Module (SIM) The SIMs can generate temporal programs of expression: Last-In First-Out (LIFO) Program

17. LIFO Program in Arginine Biosynthesis

18. First-In First-Out (FIFO) Program K xz1 >K xz2 >K xz3 K’ xz1 <K’ xz2 <K’ xz3 Time K xz1 K xz2 K xz3 K xz2 K xz1 [X] [Y] [Z 2 ] [Z 3 ] [Z 1 ]

19. Where SIMs meet FFLs  Two interconnected SIMs can be viewed as a multi output FFL 

20. Multi-input FFL in Neuronal Networks FLPASH AVD AVA Nose Touch Noxious Chemicals Nose Touch Backward movement

21. Dense Overlapping Regulon (DOR) X1X2 Y1Y2 The DORs are more dense than randomly expected

22. How do Network Motifs Integrate? The E.coli Transcription Network (partial) A single DOR Layer FFLs and SIMs are integrated within DORs A Master Regulators Layer (lots of Auto-Reg.)

23. Summary Network motifs can function in  several biological processes (sensory systems, development).  different time scales (milliseconds, cell generations). Network motifs can produce temporal programs (LIFO, FIFO, oscillation). Different kinds of network may interact to generate regulation