that migrate to tissues in response to eotaxin and release factors that damage tissues, causing some of PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/1977615 the undesirable consequences of inflammation. Once inflammation infects one cerebral artery, it may cause thrombotic or embolic occlusion. Another example is INTEGRIN2 PATHWAY. Integrins are cell surface receptors that interact with the extracellular matrix and mediate intracellular signals in response to the extracellular matrix including cellular shape, mobility, and progression through the cell cycle. Growth factor signaling pathways and the caveolin receptor exhibit important cross talk with integrin receptors in cellular responses like activation of map kinase, proliferation and motility. If some disorders occur in the process of INTEGRIN2 PATHWAY, blood vessel cell proliferation and motility may be destroyed and lead to thrombotic or embolic occlusion. Hence these pathways may give new suggestions to identify other targets in stroke. Anti-ischemic stroke effects 
of CYNA by network scores Calculating the optimal r for the CYNA. The algorithm of random walk with restart has been successfully used in the prioritization of candidate disease genes and r = 0.3 appeared to be a robust choice. Thus we took r = 0.3 to score ischemic stroke’s effect on the human PPI network in this study. Since r = 0.3 was got by fitting real data of disease genes, it may not be optimum for estimating the impact of the small molecule CYNA on the network. Therefore, we tried to find the optimal r value by the following procedure: 1. Defining targets obtained from comparative proteomic experiment as seed nodes, and then defining targets obtained from similarity search method as test set P; 2. Taking r = 0 and calculating the score for the anti-ischemic stroke effects of CYNA on the human PPI network by Eq; 3. Descendingly ranking the genes according their scores; 4. Calculating the average ranking score RS of genes in the test set P; 5. Seting r = r+0.05, and using the above procedure to obtain the corresponding RS value; Continuing to implement the PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/19778220 above procedure, we use different r values to obtain the corresponding RS values. Fig 4 shows the relationship between r and RS. It can be see that the curve of the correlation between r value and RS value is a notching curve. RS value decreases first and then increases. It reaches minimum when r = 0.1. Therefore, the optimal r value for CYNA was taken as 0.1. Network scoring anti-ischemic stroke of CYNA. The network score was computed in order to explain the anti-ischemic stroke effect of CYNA quantitatively. The targets obtained from comparative proteomics experiment and similarity search method were combined as the group of seed nodes. As a naturally-occurring substance, inhibition potency of CYNA on targets could be much weaker, unlike that of specifically designed drug molecules. Therefore, we defined the components of the initial vector x0 corresponding to targets of CYNA obtained by comparative proteomics experiment as the AMI-1 site normalized at, and the components of the initial vector x0 corresponding to targets of CYNA by similarity search method as the average of all the normalized at value, otherwise x0 = 0. Score vector xis of ischemic stroke’s effect on the human PPI network and score vector xca of the anti-ischemic stroke effects of CYNA were respectively obtained based on Eq and associated data. Then CYNA’s effect on the human PPI network was calculated by E = < xis, xca >. The effect score is 0.0589. 11