Gene Density Interactive Visual ExplorER
About Gene DIVER: Gene DIVER is a scalable implementation of a recently developed non-parameteric hierarchical cluster mining algorithm that also incorporates a powerful visualization and browsing of clusters. It is a great tool for users interested in finding pure, small, dense clusters, especially in scenarios where a large fraction of the data may not cluster well. Gene DIVER provides a new level of robustness in cluster mining with it's ability to automatically identify: (1) if there are any clusters in any part of the data, (2) (if present) where they are, (3) what they are (their member data points), and (4) how they are related to each other. Gene DIVER produces a compact hierarchy of all the discovered clusters, which can then be visualized and browsed within Gene DIVER. Areas where Gene DIVER holds great promise is Bioinformatics, and some features of Gene DIVER are specifically tailored for clustering genes. Other potential non-biological applications include market-basket data, biometrics, and web data.
Free Download (please register, see below): Click here to download a free copy. To install, simply unzip all files into a single directory. Gene diver executable file is genediverw.bat. See the lower part of this page for two demo datasets for Gene DIVER.Note: Gene DIVER needs JRE 1.5 (same as JRE 5.0) or higher that can be downloaded and installed from this page. Currently tested on Windows and AMD64 bit linux, but should work with any platform supported by Java.
Support and Registration:To better understand our users, we encourage you to register your copy of Gene DIVER by simply sending an email to firstname.lastname@example.org, with subject "register", and your name in the email body. We will only contact you if further updates or bug fixes are available, and your email will not be shared with anyone else.
Related papers and publications: To find out more about the clustering algorithm behind Gene DIVER, please see Auto-HDS website and related papers. The last chapter of this Ph. D. dissertation describes Gene DIVER in some detail, especially the scalable architecture of Gene DIVER and some of its unique user interface features that make it well-suited for finding small, pure clusters on large, high-dimensional, noisy datasets.
Test/Demo datasets for Gene DIVER: Two demo datasets are available for demostrating clustering using Gene DIVER:
Click here to visit the IDEAL LAB at University of Texas at Austin, where Gene DIVER was developed.