CLICK specifications


Unique identifier OMICS_23806
Alternative name CLuster Identification via Connectivity Kernels
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data Some fingerprint data and similarity data.
Operating system Unix/Linux
Programming languages C
Computer skills Advanced
Maintained No


No version available


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Publication for CLuster Identification via Connectivity Kernels

CLICK citation


Large scale hierarchical clustering of protein sequences

BMC Bioinformatics
PMCID: 547898
PMID: 15663796
DOI: 10.1186/1471-2105-6-15

[…] es have also been observed in other large data sets such as phone-call or web-link graphs [].An alternative approach for cluster determination is presented by Sharan et al. []. Their CLICK algorithm (Cluster Identification via Connectivity Kernels) uses graph-theoretic and statistical techniques to first identify tight groups of highly similar elements (kernels), which are likely to belong to the […]

CLICK institution(s)
Department of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
CLICK funding source(s)
Supported by an Eshkol fellowship from the Ministry of Science, Israel; by a grant from the Ministry of Science, Israel, and by the Israel Science Foundation formed by the Israel Academy of Sciences and Humanities.

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