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CODENSE specifications


Unique identifier OMICS_26407
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes


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  • person_outline Xianghong Jasmine Zhou <>

Publication for CODENSE

CODENSE in publications

PMCID: 5907309
PMID: 29671392
DOI: 10.1186/s12918-018-0533-6

[…] larger frequent subgraphs. as mentioned, these methods do not count the number of occurrences of a subgraph in a network but rather check is the subgraph appears at least once in a given network., codense [] finds coherent, dense subgraphs in large biological networks. graphsig [] mines significant and frequent subgraphs in which graphs are represented as feature vectors. sis [] finds […]

PMCID: 4151083
PMID: 25221624
DOI: 10.1186/1756-0381-7-16

[…] since the links between the edges in a given module can be scattered across the graphs but appear together in the aggregate graph. to overcome these false positive modules, hu et al. [] proposed the codense algorithm, a two-step approach for mining coherent dense subgraphs. in the first phase, dense modules are extracted from the aggregate graph. the second phase uses the edge occurrence […]

PMCID: 3854656
PMID: 24565174
DOI: 10.1186/1752-0509-7-S4-S3

[…] [] discovers frequent subnetworks of enzyme interactions in a collection of metabolic networks. it models input networks as relational networks and represents each enzyme by a unique node label. codense [] seeks coherent dense subnetworks. it also models biological networks as relational networks. nemo [] reconstructs transcription regulatory modules in a systematic and efficient manner. […]

PMCID: 4231395
PMID: 24041013
DOI: 10.1186/1752-0509-7-90

[…] may achieve better results. mcode is a heuristic algorithm developed to detect complexes in protein interaction networks []. other examples include restricted neighborhood search clustering [] and codense, an algorithm for finding dense subgraphs []. a number of algorithms based on local neighborhood statistics were proposed as well, for example to find subgraphs of ppi networks […]

PMCID: 3305748
PMID: 22536863
DOI: 10.1186/1471-2105-13-S2-S12

[…] the pcc value between them is higher than a pre-defined threshold) and transforming the network into a sparse unweighted gene co-expression network (uwgcn). for instance, in [] , an algorithm called codense was developed to identify frequent uwgcns from multiple datasets and this method has been applied to cancer biomarker discovery. issues with the uwgcn approach include how to determine […]

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CODENSE institution(s)
Program in Molecular and Computational Biology, University of Southern California, Los Angeles, CA, USA; Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA
CODENSE funding source(s)
Supported by the nih grant 1P50CA112952; the usc faculty set up grant and the NIH grant 5R01GM067243; and by NSF IIS-02-09199.

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