This is version . It is not the current version, and thus it cannot be edited.
Back to current version   Restore this version

CNetQ: Network querying tool based on conditional random fields

  • Last updated: June 7, 2011

Introduction#

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.

Reference#

  • Qiang Huang, Ling-Yun Wu, Xiang-Sun Zhang. An Efficient Network Querying Method Based on Conditional Random Fields, manuscript, 2011.

Data and code:#


There are APORC Document Center : CNetQ - Plugin insertion failed: Could not find plugin org.goodjava.plugin.hitcounter.HitCounterAPORC Document Center : CNetQ - Plugin insertion failed: Could not find plugin org.goodjava.plugin.hitcounter.HitCounter visitors since June 7, 2011

More Software ...

Add new attachment

Only authorized users are allowed to upload new attachments.

List of attachments

Kind Attachment Name Size Version Date Modified Author Change note
7z
code.7z 77.8 kB 3 30-Sep-2011 17:40 LingyunWu Modification to use UGM instead of CRFall
7z
data.7z 239.3 kB 2 27-Aug-2011 14:27 LingyunWu
« This particular version was published on 07-Jun-2011 18:59 by LingyunWu.