DKernel uses Diffusion Kernel algorithm to propagate sub-network for pathway analysis, disease vicinity, social network, etc.
### Background Information Diffusion Kernel is a network propagation algorithm, as you first see the name, one substance that probably comes out of your mind is fluid, like water, air. Diffusion is a process that flows of matter permeates from a high concentration region to the lower one. In the process of network analysis, you could imagine the subgraph you have selected as the water supply pump. It will reach out to every node until the influx rate equals outflux for each node, which is called the equilibrium state, and there is a loss parameter for you to customize the scale of the diffusion. ### DKernel profile DKernel is the abbreviation for the diffusion kernel algorithm. You can apply it in various fields, including exploring pathways for disease genes, social networks, etc. Work with Cytoscape 3.8 and above. Features: 1. A customized parameter for user to delimit the diffusion scope. 2. You are treated to a superb display of colorful layout supported by the palette. 3. Scores are embeded in the node table for checking or exporting. There will be updates on my blog if there are new features for DKernel, and you could navigate the site by clicking the button ''Website" on the right panel. For more information, please refer to the tutorial. Please feel free to contact me by email. Haotian Bai, CS school at Shanghai University ### References 1. Qi Y, Suhail Y, Lin Yy, Boeke JD, Bader JS. Finding friends and enemies in an enemies-only network: a graph diffusion kernel for predicting novel genetic interactions and co-complex membership from yeast genetic interactions. Genome research, 18:1991–2004, 2008.


Works with Cytoscape 3.7

Release Notes

the initial commitment for bug fix


Works with Cytoscape 3.7


Version 1.1

License Click here

Released 20 Aug 2020

Works with Cytoscape 3.7

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