Hierarchical Clustering R Software

Efficient analysis of complex networks using hierarchical clustering. If you use Jerarca, please cite: Aldecoa R, Mari­n I (2010) Jerarca: Efficient analysis of complex networks using hierarchical clustering PLoS ONE 5(7):. ...

ClusterLib was designed as an Open Source library that can be used for agglomerative hierarchical clustering. ClusterLib can work with arrays of Java's Double as well as with other custom data types. In principle, any class implementing the. ...

brCluster is a class library, written in java, that implements generic clustering algorithms carefully designed to allow its aplication in any kind of data. The algorithms implemented are K-means and Hierarchical Clustering (Simple and Complete. ...

A code in C++ for identifying clusters in a multi-dimensional space. It computes a locally adaptive metric so as to maximize the information content from the data and then implements density based hierarchical clustering algorithm.

A hierarchical clustering package for Scipy. hcluster is a library that provides Python functions for hierarchical clustering.The interface is very similar to MATLAB's Statistics Toolbox API to make code easier to port from MATLAB to Python/Numpy.

VisualStat is a major integrated development environment for R. It incorporates all the descriptive statistics, parametric and nonparametric statistical methods, charts and data transforms you will need for analyzing and presenting data.

MEFIT. MEFIT is a Microarray Experiment Functional Integration Technology. Given any amount of microarray data, it predicts the probability of pairwise functional relationship for any gene pair within individual biological functions.

CLC Main Workbench 5.6.1 provides you with a software environment which enables users to make a large number of advanced DNA, RNA, and protein sequence analysis, combined with gene expression analysis, smooth data management, and excellent graphical. ...

XLSTAT is a complete data analysis and statistics add-in for Excel. It includes regression (linear, logistic, nonlinear), multivariate data analysis, parametric tests, non parametric tests, ANOVA, ANCOVA, forecasting methods.

In this project, an architecture involving several clustering techniques has to be built like complete-link clustering, group-average agglomerative clustering and centroid clustering, spectral clustering.

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical. ...

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical. ...