Category Intelligent Software>Data Mining Systems/Tools

Abstract Panmo is an interactive, dynamic visualization system with a set of advanced tools for statistical analysis. It uses an intuitive user interface to empower users to extract information from large, complex, multivariate data sets quickly, effectively, and with confidence.

Panmo utilizes graphics extensively because graphics can let the data talk for itself and convey more information than simple numeric summaries.

Graphics is also an integral part of its user interface.

Panmo allows users to look at a plot and, by interacting with graphical symbols in the plot, retrieve data from the database. The data so retrieved can be passed to functions of the system by interactive graphics.

The data retrieved and the analysis results generated in this way can be in the form of plots again and ready for further graphical manipulation and query.

Panmo can be used anywhere you would like to explore and make the most out of your data.

For example, high-content screenings (HCS), functional genomics, drug discovery, ecology, risk management, etc.

Panmo features/capabilities --

Incorporating recent advances in statistical computing, computer graphics, machine learning, and user interface design, Panmo has the following features:

1) Tools to generate information-rich visualizations – Scatter plot, 2D histogram, box plot, table plot, histogram, bar plot, variable resolution bivariate plot, Tukey sum-difference plot, profile plot (or parallel coordinate plot), X-rayed profile plot, 3D point cloud rotation, various types of trellis graphs, and 'browse'.

(This is a smart tool. It knows what plots to draw No matter how many and what types of variables are passed to it. It dramatically cuts down the cognitive effort required during graphical query formulation because users don't have to worry about what types of plots to look at. All they have to do is know what variables to look at).

2) Advanced numerical tools - SOM (Self-Organizing Map), K-means, hierarchical clustering, principal component analysis (PCA), classification and regression trees, sign test, Minimal spanning tree planing (also known as multivariate planing), multivariate Smirnov test, various profile searching tools, and lowess smoothing.

All these numerical tools present their result graphically and are seamlessly integrated with the products intuitive user environment via dynamic graphics.

3) Reporting tools - PostScript/PDF files of publishing/production quality and PNG images can be generated at the click of one finger tip. The whole flow of data analysis and user's 'train of thought' can be recorded and published on the internet.

4) Multi-window interactive dynamic graphics - Visualizing big and complex data sets using a single display window is difficult at best. Multiple windows are used in Panmo to provide users with simultaneous multiple views into data space.

Each display window serves as a 2-way communication link between the system and users: the system shows data in display windows and users can look at a display window and, by interacting with graphical symbols in the display window, issue commands to the system.

5) Focusing and linking - To display complicated information, like that contained in a big and complex data set, a common instinct is to draw a plot that is equally complicated, such as presenting the data as a tableau of Chernoff faces. Attempts at such dense encoding are seldom successful.

It is usually more effective to construct a number of simple, easy to understand plots, each focused clearly on a particular aspect of the underlying data. Each plot conveys partial information about the data.

Panmo integrates the information in multiple plots into a coherent image of the data as a whole by linking the contents of individual plots. Painting is one of many interactive techniques available in Panmo to link contents in plots.

6) Graphical query formulation - Panmo considers components of plots as visual representations of underlying entities (e.g., cells, credit card customers, data sets, etc.), which opens entirely new possibilities for interaction.

With such an arrangement, users can look at a plot and, by interacting with graphical symbols in the plot, initiate the retrieval of data from the underlying database.

Analysis routines to be applied to the data can be selected graphically. The results of the analysis or data retrieval can again be in the form of plots and ready for further graphical manipulation.

With Panmo, if you see any pattern of interest in a plot, you can retrieve the data generating the pattern immediately.

Panmo's way of graphical query formulation is especially useful when there are patterns that are apparent in plots but are tedious or difficult to describe with a textual query language.

7) The most advanced graphics to cope for over-striking - As a more sophisticated measure to cope for over-striking in scatter plots, the novel variable resolution bivariate plots (or Varebi plots for short) in Panmo deals with the problem of over-striking, by mixing the display of a density estimate and the display of individual observations.

The idea is to determine the display format by analyzing the actual amount of over-striking on the screen. Thus, the display format will depend on the sample size, the distribution of the observations, the size and shape of individual icons, and the size of the window.

It may change automatically when the window is resized. Varebi plots reveal detail wherever possible and show the overall trend when displaying detail is Not feasible.

8) Logical zooming - There are two (2) types of zooming: geometric zooming and logical zooming. Geometric zooming produces a blown up version of the region in which each pixel in the source image is represented by a small square of the same color.

Logical zooming produces a plot based on the actual observations in a source region. As a result, more details can be revealed.

9) On-line context help; 10) Object-oriented data representation - Object- oriented data representation allows easy mapping of ‘conceptual entities’ in the problem domain into computational entities in the system domain.

11) Three layers of user interface – The user interface of Panmo consists of graphical direct manipulation, menus, and textual commands.

12) Smart menu system - Panmo knows what type of menu to use for a tool and only includes relevant items in the menu.

13) Inspection - Users can click any graphical icon and get detailed information on data they represent.

14) HCS image module - With this module, all plots are fully linked to the original scan images. You can get the original scan images of the cells from any graphical symbols in any plots.

Data of any cells in a scan image can be instantly retrieved to pass to any analytic function or to make any plot.

15) HCS impressionist density plot module - Impressionist density plots provide a compact, eye-pleasing way to compare the data from different treatments in HCS experiments.

Note: The combined power of Panmo's tools and operations working together is multiplicative, instead of being additive in traditional informatics systems.

System Requirements

Microsoft Windows NT4.0/2000/XP/Vista

Linux (x86)


Manufacturer Web Site Panmo

Price Contact manufacturer.

G6G Abstract Number 20355

G6G Manufacturer Number 104005