Search Results for "cluster analysis"

Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types.

Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional...

AWclust is easy to use non-parametric population structure analysis software written for R with a GUI interface. Just point and click and you will be on your way to discovering the important cluster information in your SNP data sets.

IMPORTANT: The project moved over to github! You can find it at: https://github.com/exhuma/python-cluster

This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs...

Clown is a "clustering" framework. It allows you to cluster datasets (in ARFF) format using a number of different clustering algorithms.

Facelift is a visualization and analysis software for online social networking services. It displays a given community as a node-link diagram and provides several search / filtering functions as well as cluster analysis features.

The CHIP Cluster Generator attempts to create spatio-temporal cluster data in an automated fashion to help evaluate epidemic detection software. The spatio-temporal data will then be used to determine robustness of spatial detection algorithms.

clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.