1. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 1 PNAS 101 2981, 2004 http://www.pnas.org/cgi/reprint/0308661100v1 Predicting Complex Biological Networks Studying networks represent a move from a fairly static, model of life (genome sequence) to a more dynamic, processes-oriented approach to life.

2. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 2 http://www.cs.tau.ac.il/~spike/ Superposition of Gene Expression Data on Signaling Networks

3. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 3 http://genomics.energy.gov/gallery/b2b/gallery-02.html Networks and Simulations

4. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 4 Andrade et al., In Silico Biol. 6, 495 (2006; Figure 2) http://www.bioinfo.de/isb/2006060046/ Input data 300 protein sequences 15,000 protein sequences 33,869 protein sequences 126,318 BlastP searches 6,805,323 BlastP searches 15,186,996 BlastP searches Analysis using hardware platform For relatively small input data sizes (300 protein sequences), a local cluster and a single CPU surpass the Grid solution. 1,304 hrs 22 hrs Large Scale Computations-Overcome the Bottleneck

5. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 5 Are We Done ? “Now this is not the end. It is not even the beginning of the end. But it is perhaps, the end of the beginning”. Winston Churchill, 1942 (3 years into WW2) http://www.globecartoon.com/neweconomy/10.html 5

6. Metsada Pasmanik-Chor, TAU Bioinforamtics Unit 6 metsada@bioinfo.tau.ac.il tel: 03 640 6992 Goal: Make bioinformatics tools readily available to experimentalists http://www.tau.ac.il/lifesci/bioinfo/