1. Seminar in Bioinformatics (236818) Ron Y. Pinter Fall 2007/08

2. Why? Really … Advanced Algorithms in Computational Biology II –Can’t fit everything in one term –Not just sequence alignment, HMMs, and Bayesian networks Ever evolving and changing needs and ideas Still, trying to focus on some specific area

3. What? Pathway and Network Analysis Genome Rearrangements Protein and RNA Structure PredictionProtein and RNA Structure Prediction Expression analysis (Zohar Yakhini)Expression analysis (Zohar Yakhini) Linkage analysis (Dan Geiger)Linkage analysis (Dan Geiger) Phylogenetic analysis (Shlomo Moran)Phylogenetic analysis (Shlomo Moran)

4. Biological Networks Networks are a powerful method for describing and analyzing the relations among entities Used in Computer Science, Operations Research, Electrical Engineering, etc. We use them to model the complexities of large biological systems

5. Some Networks protein-protein interactionsgene regulation

6. Pathways Focus on a particular function The “blue print” of cellular processes Smaller scale than networks, but they contain a lot of detailed information

7. Some Pathways a signaling pathwaya mixed pathway

8. Interesting Static Properties Structural similarity Functional similarity Comprise (small) basic building blocks –what are they? –how do they compose? …

9. Interesting Dynamic Properties Quantitative –kinetics –concentrations –expression levels –… Qualitative –robustness –stability –convergence –oscillation –transient expression –fail-safety (sensitivity) –…

10. Modeling and Analysis Methods Labeled graphs Networks – Boolean, discrete, continuous [Hybrid Functional] Petri Nets (HFPN) ODEs/PDEs Various calculi and process algebras Flux Balance Analysis (FBA)

11. When to Use What? For static analysis –graph algorithms –algebraic methods –statistical tests For dynamic analysis –detailed behavior – ODEs –qualitative behavior – networks –some specific properties – various calculi

12. A Few Examples Static –[Seeded] Alignment of Metabolic Pathways (Pinter et al., Bioinformatics, 2005; Lozano et al., WABI 2007) –Integrative Analyses of Interaction Networks Underlying the Cellular Circuitry in Yeast (Yeger-Lotem et al., PNAS 2004) –Elucidating Protein Function using Graphlet Degree Vectors in Prtoein- Protein Interactions Networks (Gordon et al., under review). Dynamic –HFPN-based Simulation of the Reduced Folates Metabolic Pathway (Assaraf et al., JTB 2006) –Faithful Modeling of Transient Behavior in Developmental Pathways (Rubinstein et al., PNAS 2007) Both –Flux Based vs. Topology Based Similarity of Metabolic Genes (Rokhlenko et al., WABI 2006; Bioinformatics 2007)

13. 4-protein motifs as combinations of 3-Protein Motifs ABCD A B C D

14. Topics 1.Static analysis of metabolic pathways 2.Network motifs: discovery and applications 3.Flux balance analysis of metabolic pathways 4.Pathway modeling and simulation 5.Dynamic analysis of small networks 6.Analysis of genomewide networks

15. When, where and who? Time and Place –Monday, 16:30am-18:30pm, Taub 4 Staff –Prof. Ron Pinter, pinter@cs.technion.ac.il, x4955, Taub 705; Office hours: Tuesday, 10am-12noonpinter@cs.technion.ac.il –Itai Sharon, itaish@cs.technion.ac.il, x4946itaish@cs.technion.ac.il Site http://webcourse.cs.technion.ac.il/236818/

16. How? References –Uri Alon: An Introudction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall, 2006. –Bernhard Ø. Palsson: Systems Biology: Properties of Reconstructed Networks. Cambridge University Press, 2006 –Darren Wilkinson: Stochastic Modelling for Systems Biology. Chapman & Hall, 2006. Duties –attendance (10%) –presentation (40%) –critical review (50%) Prereqs –course in algorithms (234246 or 234247) –background in bioinformatics (236522 or 236523)