Application of SAGA for Matching Biological Pathways

SAGA stands for Substructure Index-based Approximate Graph Alignment. It is an efficient tool for approximate subgraph matching. SAGA allows users to match a query graph against a large database of graphs. At the core of SAGA is a flexible graph distance model that incorporates node approximate matching, node insertion and deletion, as well as approximate structure matching. A powerful indexing method is implemented to speed up the matching process. Some applications of SAGA include querying/comparing pathways and querying parsed biomedical literature databases to find similar documents.

Right now, we provide 2 pathway datasets that the users can query against. The datasets are described below: ** UPDATED on Jan 11, 2008 **

Database Size Description
KEGG Human Pathways (downloaded on Dec 5, 2007) 198 Pathways KEGG Human Metabolic Pathways and Human Regulatory Pathways.
All KEGG Pathways (downloaded on Dec 5, 2007) 65,455 Pathways All pathways of the 731 species in KEGG.

Start A Query:

Please Choose the Database:

    ** UPDATED on Jan 11, 2008 **

Please Upload the Query File: [File Format] [Sample File 1] [Sample File 2]

We provide some scripts translating other graph formats into SAGA format. ** UPDATED on Nov 3, 2007 **

   

Enter the Required Percentage of Matched Nodes:

    %


If you have any questions or suggestions, please contact ytian [at] umich [dot] edu or jignesh [at] umich [dot] edu

Last updated Jan 11, 2008.