Advanced clustering techniques in Vortex can be visualised with the dendrogram viewer.  Combined with the grid view clusters of compounds can be trivially selected by folding in or removing branches with single clicks.

Jython is a Java implementation of the Python scripting language.  Using Jython whole new plot types can be created.  Shown here is one of the examples available from the Dotmatics support pages.  The chart is fully interactive with any other chart displayed in Vortex with filter and selection behaviour being replicated.

Make trawling your HTS data easier with this plate viewer.  We have no hard definitions as to the shape of your plates.  Colour by any properties or calculated values.  Spot trends easily across your assays.

Vortex has full support for recursive SMARTS and using this technology a novel fingerprinting methodology has been developed called DotFP.  DotFP builds sets of fingerprint bits that represent the presence of chemical fragments.  Fragments identified by the fingerprinting technique can be visualised directly in the Vortex Chemistry Data Table.  Clustering can be done within Vortex using DotFP, imported third-party fingerprints or any other non-fingerprint properties.  Clusters can be visualised and browsed with the dendrogram plot type.  Fingerprints can also be used for Tanimoto calculations.

Vortex automatically integrates with ISIS/Draw, ChemDraw, Marvin Sketch and JME for substructure entry.  Files can be imported from Microsoft Excel and plots exported to Powerpoint.  Example integration with R statistics, Pipeline Pilot and others are available to download on the support pages.  Activity Base, ISIS/Base, Accord Enterprise Informatics, Symyx/MDL Direct and other database tools can be integrated with Vortex via Browser.

With a rich palette of plot types, filter devices and an editable table of data Vortex enables your scientists to rapidly identify outliers and spot trends in multi-dimensional data.

Here is a convenient way of graphically depicting groups of numerical data through their five-number summaries.  Box plots can be useful to display differences between populations without making any assumptions of the underlying statistical distribution: they are non-parametric.

Box plots are not skewed

by outliers as the

whiskers relate to the

distance between the

lower and upper

quartiles of the

distribution.

One fundamental feature of Vortex is the ability to load tables of chemistry data.  Substructure querying is built right into the client for SDF data and columns of SMILES.  Advanced property calculation for molecular weight, XLogP, TPSA, hydrogen bond acceptor and donor counts and others make finding your key compounds simple.

Build rich interfaces to your custom scripts through Java Swing.  Many examples provided with product provide ideal starting points for your own creations.

New columns can be calculated with complex functions.  These can be added via the scripting menu.  Several simple examples are provided with the product to illustrate how to calculate differences between two columns and more complex functions such as a ligand efficiency calculator.

As a user selects points in a plot drill down reports can be made available.  In the example here a report from Browser is presented.  Using a simple mechanism other tools such as Pipeline Pilot or SharePoint can be integrated into the drill down.

Target selectivity is key to the success of a drug project.  The Vortex Kinome plot type provides a visual and intuitive way of analysing your organisation’s systematic screening efforts across hundreds or thousands of compounds. 

Scatter plots

in 2D or

3D can be

annotated

with structural

depiction,

regression

lines (linear,

EC50 etc),

background

images, group

lines and more.

Data points

can be tagged

with colour, labels, size, transparency, symbol and have mouse over events such as display URLs attached.  Plots can be freely annotated to flag interesting areas in the design mode.  Annotations are saved in templates for reuse.  When zooming a scatter plot the plot really is zoomed and not filtered as in some other data visualisation products.