1. Discrete Methods for the Modeling and Analysis of Biological Networks and Pathways
Ron Y. Pinter
December 9, 2018

2. Biological Networks
Networks are a powerful tool for describing and analyzing relations among entities
Used extensively in Computer Science, Operations Research, Electrical engineering, Physics, Sociology, Behavior, Economics, Neuroscience etc.
We use them to model and analyze the complexities of small and large biological systems

3. And also
Computational geometry
Compiler technology

4. Some Biological Networks
protein-protein interactions
Transcription regulation

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

6. Some Pathways
a signaling pathway
a mixed pathway

7. Interesting Static Properties
Structural (topological) properties (clustering coefficient, betweenness, centrality, degree distribution) allow us to examine similarity and perform classification
Comprise (small) basic building blocks
what are they (motifs)?
how do they compose?
Inferred Functional properties

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

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

10. A Few Examples Static Dynamic Both
Integrative Analyses of Interaction Networks Underlying the Cellular Circuitry in Yeast (Yeger-Lotem et al., PNAS 2004)
[Seeded] Alignment of Metabolic Pathways (Pinter et al., Bioinformatics, 2005; Lozano et al., WABI 2007)
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)

11. 4-protein motifs as combinations of 3-Protein MotifsD A B C D

12. Dynamic analysis of small networks
Faithful Modeling of Transient Behavior in Developmental Pathways (Rubinstein et al., PNAS 2007)

13. My Track record
10 Ph.D. theses in 9 years +7 M.Sc. Theses in parallel some interdisciplinary

14. Thesis Topics
I Computational biology: 1. Add the effect of short RNA to the gregNetsim model
II Computational Systems biology :
2. Adding signaling networks to the integrated analysis to find motifs with 3 types of edges Finding mixed motifs distinguishing between positive and negative regulation
4. Efficient computation of Graphlet Degree Vectors (GDVs)
5. Factoring a biological network (PPI or gReg networks) to its basic building block in a top-down approach by finding biconnected and triconnected components; this is better than the motif approach of Alon et al. which is limited to small networks (since it is bottom up) 
6. Adding small RNAs to the gRegnetsim model
7. Comparing the phenotype-based traditional taxonomy to phylogenetics trees

15. Thesis Topics (cont’d)
III Computational geometry: 8. Optimal routing of 2-pt nets across a channel in the one layer/net model
(combining river routing with permutation graph coloring – with Shmuel Wimer) 9. Solve the rectangulation counting with pin-wheels
IV Compiler technology: 10. Debugging of optimized code 11. memoization of functions with more than one argument possibly with currification (ditto re coadvisors)
V Algorithms:
12. Seeded optimization
13. Efficient computation of Euler’s totient function with memoization (number theory)
14. Some of the above network topics

16. Other Contributions
M. A. Bender, D. Ge, S. He, H. Hu, R. Y. Pinter, S. Skiena, and F. Swidan: "Improved Bounds on Sorting by Length-Weighted Reversals"; Journal of Computer and System Sciences, Vol, 74, No. 5 (August 2008), pp
Firas Swidan, Michael Shmoish, Eduardo Rocha, and Ron Y. Pinter: "An Integrative Method for Accurate Comparative Genome Mapping"; PLoS Computational Biology, Vol. 2., No. 8 (August 2006), pp
Adi Mano, Tamir Tuller, Oded Beja, Ron Y. Pinter: “Comparative Classification of Species and the Study of Pathway Evolution based on the Alignment of Metabolic Pathways"; BMC Bioinformatics, Volume 11 Suppl 1 (selected papers from APBC), January 2010.
Ron Y. Pinter a, Oleg Rokhlenko , Dekel Tsur "Approximate Labelled Subtree Homeomorphism”; Journal of Discrete Algorithms No. 3 (September 2008),
Partial Information Network Queries

17. Other Contributions (cont’d)
Ariel Miller, Nili Avidan, Noa Tzunz-Henig, Lea Glass-Marmor, Izabella Lejbkowicz, Ron Y. Pinter, and Tamar Paperna: "Translation towards Personalized Medicine in Multiple Sclerosis"; Journal of the Neurological Sciences,Vol. 274 (2008), pp
Alexandra Skolozub, Ofer Sarig, and Ron Y. Pinter: "Conditional Pathway Integration”; Proceedings of the 8th Annual International Conference on Computational Systems Bioinformatics (CSB), August 2009, pp
Alon Diament, Ron Y. Pinter and Tamir Tuller: “Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function” Nature Communications Article number: 5876 (December 2014)
Dolev Dotan and Ron Y. Pinter: "HyperFlow: an Integrated Visual Query and Data-Flow Language for End-User Information Analysis"; Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC'05), September 2005, pp

18. Other Contributions (cont’d)
Martin Akerman, Hilda David-Eden, Ron Y. Pinter, and Yael Mandel-Gutfreund: "A computational approach for genome-wide mapping of splicing factors binding sites"; Genome Biology,, Vol. 10, No. 3 (March 2009)
Y. Aumann, M. Lewenstein, O. Melamud, R. Y. Pinter, and Z. Yakhini: "Dotted Interval Graphs and High Throughput Genotyping"; ACM Transactions on Algorithms, (Vol. 8, No. 2), Article 9,  April2012, pp
Meirav Zehavi, Dor Ganor and Ron Y. Pinter: GRegNetSim: “A Tool for the Discrete Simulation and Analysis of Genetic Regulatory Networks” in print
Metagenomics
Sharon I, Bercovici S, Pinter R.Y., and Shlomi T. "Pathway-based functional analysis of metagenomes". Journal of Computational Biology; Vol.18, No.3 (March 2011) pp
Sharon, I., Battchikova, N., Aro, E.-M., Giglione, C., Meinnel, T., Glaser, F., Pinter, R.Y., Breitbart, M., Rohwer, F., and Beja, O. (2011) "Comparative metagenomics of microbial traits within Oceanic viral Communities. ISME J. (2013)

19. Key Success Factors for interdisciplinary Research
Speak the same language
Mutual respect
Joint supervision of graduate students