:: DESCRIPTION
LUMIWCLUSTER is an R package that implements a weighted model based clustering for Illumina BeadArray Methylation Assays.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Kuan, P., Wang, S., Zhou, X., and Chu, H. (2010).
A statistical framework for Illumina DNA methylation array.
Bioinformatics, 26 (22): 2849-2855.
:: DESCRIPTION
hclust demonstrates the usage of Hopfield networks for clustering, feature selection and network inference.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Bioinformatics. 2014 May 1;30(9):1273-9. doi: 10.1093/bioinformatics/btt773. Epub 2014 Jan 8.
Characterizing cancer subtypes as attractors of Hopfield networks.
Maetschke SR1, Ragan MA.
:: DESCRIPTION
EFC (Evolutionary Fuzzy Clustering) is able to deal with overlapping clusterings.
::DEVELOPER
The Centre for Integrative Bioinformatics VU
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Van Houte, B.P.P. and Heringa, J. (2010).
Accurate confidence aware clustering of array CGH tumor profiles.
Bioinformatics, 26(1): 6-14
:: DESCRIPTION
ESPRIT-Tree is a software for hierarchical clustering analysis of massive sequence data.
::DEVELOPER
Bioinformatics Laboratory, SUNY Buffalo
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Y. Cai and Y. Sun
ESPRIT-Tree: Hierarchical Clustering Analysis of Millions of 16S rRNA Pyrosequences in Quasilinear Time,
Nucleic Acids Research, vol. 39, no. 14, e95, 2011. (impact factor: 7.8)
:: DESCRIPTION
CFinder offers a fast and efficient method for clustering data represented by large graphs, such as genetic or social networks and microarray data. CFinder is a free software for finding overlapping dense groups of nodes in networks, based on the Clique Percolation Method, CPM, of Palla et. al. Nature (2005).
::DEVELOPER
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
CFinder: locating cliques and overlapping modules in biological networks.
Adamcsek B, Palla G, Farkas IJ, Derényi I, Vicsek T.
Bioinformatics. 2006 Apr 15;22(8):1021-3. Epub 2006 Feb 10.
:: DESCRIPTION
CLIC is a computational tool for helping users identify new members of a pathway of interest, as well as the RNA expression datasets in which that pathway is relevant.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Li Y, Jourdain AA, Calvo SE, Liu JS, Mootha VK.
CLIC, a tool for expanding biological pathways based on co-expression across thousands of datasets.
PLoS Comput Biol. 2017 Jul 18;13(7):e1005653. doi: 10.1371/journal.pcbi.1005653. PMID: 28719601; PMCID: PMC5546725.
:: DESCRIPTION
rsgcc is an R package that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Plant Physiol. 2012 Sep;160(1):192-203. doi: 10.1104/pp.112.201962. Epub 2012 Jul 13.
Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.
Ma C1, Wang X.
:: DESCRIPTION
ClusterProject is a program that provides a computational and graphical environment for analyzing data from DNA microarray experiments, or other corresponding cluster datasets. This software with a graphical user interface contains various clustering methods (ten agglomerative hierarchical methods, one divisive hierarchical method and three partitional clustering methods), various similarity metrics, and the evaluation metrics, as well as multi-variant analysis including PCA and the mixed model approach.
::DEVELOPER
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Genomics Proteomics Bioinformatics. 2005 Feb;3(1):36-41.
Clustering gene expression data based on predicted differential effects of GV interaction.
Pan HY, Zhu J, Han DF.
:: DESCRIPTION
SEED is a software for clustering large sets of Next Generation Sequences (NGS) with hundreds of millions of reads in a time and memory efficient manner. Its algorithm joins highly similar sequences into clusters that can differ by up to three mismatches and three overhanging residues.
::DEVELOPER
:: SCREENSHOTS
n/a
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
SEED: efficient clustering of next-generation sequences.
Bao E, Jiang T, Kaloshian I, Girke T.
Bioinformatics. 2011 Sep 15;27(18):2502-9. doi: 10.1093/bioinformatics/btr447. Epub 2011 Aug 2.
:: DESCRIPTION
M-pick is a modularity-based clustering method for OTU picking
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2013 Feb 7;14:43. doi: 10.1186/1471-2105-14-43.
M-pick, a modularity-based method for OTU picking of 16S rRNA sequences.
Wang X1, Yao J, Sun Y, Mai V.
