DSD is a program that calculates diffusion state distances between nodes in a graph. It makes use of global topologies via random walks and captures proximity between nodes in terms of node properties such as protein functions among protein-protein interaction graph. If you use DSD, please cite:
Cao M, Zhang H, Park J, Daniels NM, Crovella ME, Cowen LJ, Hescott B. (2013) Going the Distance for Protein Function Prediction: A New Distance Metric for Protein Interaction Networks. PLoS ONE 8(10): e76339. doi:10.1371/journal.pone.0076339 .
There is also an online server where you can calculate DSD: http://dsd.cs.tufts.edu/server/. DSD is licensed under the GNU public license version 2.0. If you would like to license DSD in an enviroment where the GNU public license is unacceptable (such as inclusion in a non-GPL software package) comercial DSD licensing is available through Tufts offices of Technology Transfer. Contact firstname.lastname@example.org or email@example.com for more information. Contact firstname.lastname@example.org for issues involving the code itself.
Please note that this version only handles unweighted graphs. If you have edge weights, instead please use the "cDSD" package from http://dsd.cs.tufts.edu/capdsd
M. Cao, C. M. Pietras, X. Feng, K. J. Doroschak, T. Schaffner, J. Park, H.
Zhang, L. J. Cowen and B. Hescott,
New directions for diffusion-based network prediction of protein function:
incorporating pathways with confidence
New! Enrico Maiorino has kindly contributed a new optimized python script that computes the DSD matrices much faster: you can obtain his code here: https://github.com/reemagit/DSD
Online Computing Server:
DSD Version 0.50:
Source: DSD-src-0.50.tar.gz, DSD-src-0.50.zip.
Readme (Also included in all archives)
Data used in the paper are as follows:
Physical PPIs from BioGRID
(BioGRID official website is here)
MIPS First Level Annotation
MIPS Second Level Annotation
MIPS Third Level Annotation
Note: the MIPS FunCat mapping between indices and categories is here