Search Results for "hierarchical clustering in matlab"

hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix.

...Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. ...

NOVA is a program designed to analysis complexome profiling data (Heide et al., 2012). A graphical user interface (GUI) provides various visualization tools, such as heat maps and 2D plots. Several hierarchical clustering algorithms (e.g., single linkage, average linkage, Wards linkage), different distance measures (e.g., Euclidean distance, Manhattan distance, Pearson distance), and various normalization techniques are implemented. Many additional functions like zooming, searching for proteins, image export, and automatic file format recognition support intuitive handling for biologists. ...

...The pipeline uses state-of-the-art tools and can run on various platforms with minimal configuration overhead. The pipeline enables the extraction of knowledge from typical RNA-seq studies by generating interactive principal component analysis (PCA) and hierarchical clustering (HC) plots, performing enrichment analyses against over 90 gene set libraries, and obtaining lists of small molecules that are predicted to either mimic or reverse the observed changes in mRNA expression.

Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.

The final build of this software now is distributed in R, embedded in "RedeR': an R/Bioconductor package for hierarchical and nested network analysis... more about RedeR: http://bioconductor.org/packages/2.9/bioc/html/RedeR.html

The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.

rendering flow maps with hierarchical clustering.