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CNetQ: Network querying tool based on conditional random fields

  • Last updated: October 21, 2011


A large amount of biomolecular network data for multiple species have been generated by high-throughput experimental techniques, including undirected and directed networks such as protein-protein interaction networks, gene regulatory networks and metabolic networks. There are many conserved functionally similar modules and pathways among multiple biomolecular networks in different species, therefore, it is important to analyze the similarity between the biomolecular networks. Network querying approaches can efficiently discover the similar subnetworks among different species. However, many existing methods only partially solve this problem. A novel approach for network querying problem based on conditional random fields (CRF) model is proposed, which can handle both undirected and directed networks, acyclic and cyclic networks, and any number of insertions/deletions. The CRF method is fast and can query pathways in a large network in seconds using a PC.



R package#

The network querying method has been implemented as function net.query in R package Corbi, which can be found at R-Forge:

To install this package directly within R, type:

install.packages("Corbi", repos="")

Web service#

The online version of CNetQ is available at

Matlab code and data#

The Matlab code and data used in the paper published in Bioinformatics (2011):
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List of attachments

Kind Attachment Name Size Version Date Modified Author Change note
code.7z 77.8 kB 3 30-Sep-2011 17:40 LingyunWu Modification to use UGM instead of CRFall
data.7z 239.3 kB 2 27-Aug-2011 14:27 LingyunWu
« This particular version was published on 20-Nov-2011 22:02 by LingyunWu.