Data visualisation in StarDrop

StarDrop can instantly display a comprehensive range of visualisations. You can view multiple charts simultaneously, all of which are interactively linked to one another and the underlying data, enabling you to explore the relationships between multiple properties and compound structures.

Introduction to data visualisation in StarDrop

The best methods for your projects

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Charts and dashboards

StarDrop’s drug discovery data visualisation provides a wide variety of chart types, including:

Box plots
SAR and category plots
2D and 3D scatter plots
Radar plots
Heat maps
Pie charts
Line and multi-line plots
ROC curves

You can include multiple data sets and series in the same chart, represent additional properties by colour, point, size and symbol, border or transparency, and trellis charts to highlight relationships between compounds, properties and data sets.

With StarDrop you can instantly zoom, pan and rotate your charts to spot important relationships. Explore your data further by interactively selecting interesting compounds or filter the data in your charts by multiple properties. Compounds of interest can be annotated and labelled and you can also customise your charts with different fonts, ready for inclusion in your reports or publications by simple copy and paste.

A selection of the charts and graphs you can make with StarDrop.

Chemical space

StarDrop’s unique 2- and 3-dimensional chemical spaces enable you to easily explore the distribution of properties or scores across the diversity of chemistry in your project and consider the impact of different compound selection strategies.

  • Multiple data sets: compare different chemical series and thousands of data points
  • Flexible: create chemical space projections based on structure or properties
  • Easy visualisation: set colour, symbol, size, border and transparency of points in the plot, according to properties or scores to identify ‘hot spots’ of high quality compounds and narrow down your choices quickly
  • Selection: quickly and easily select sets of compounds with a balance of properties while spreading risk across different chemistries
  • Get more detail: see a compound’s structure by hovering over the corresponding point and click for more detail or further analysis
NK2 chemical space plot

Information-rich SAR plots

With StarDrop you can create information-rich structure-activity relationship (SAR) plots, enabling you to visualise the impact of variations to R-groups, fragments or linkers on the properties of compounds within a chemical series.

StarDrop’s visualisation capabilities include the ability to display various chart types within each cell of an SAR plot including:

  • Heat maps
  • Radar plots
  • 2D scatter plots
  • Pie Charts

You can represent additional properties by colour and size, and trellis charts to highlight relationships between compounds, properties and data sets.

SAR plot


Cluster groups of ‘similar’ compounds together, for example to identify chemical series within a data set of diverse compounds, analyse SAR around hits for triaging results from high throughput screening or to identify ‘regions’ of chemistry that may yield good properties or scores.

StarDrop provides three different approaches to defining clusters:

  • Maximum common substructure
  • Compound similarity
  • Properties
Compounds can be grouped by cheical similarity as shown on these Card View stacks, so that property trends and patterns in chemical series can be identified

Data visualisation resources

Interested in better data visualisation?

If you’d like to try data visualisation in StarDrop, simply complete the form and the team will be happy to have a chat to understands your needs.

Why StarDrop?

With its comprehensive suite of integrated software, StarDrop delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop enables a seamless flow from the latest data through predictive modelling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the discovery process.