SciExpert service
Data Visualization
Publication-ready figures that read at a glance
Charts and diagrams built to journal specification — correct sizing, typography and colour, exported at the resolution the publisher wants.
- • Publication figures in R (ggplot2), Python (matplotlib/seaborn) and GraphPad Prism
- • Custom colour palettes, typography and layouts matching journal guidelines
- • Multi-panel figures with shared legends, highlighting and annotations
- • Forest plots, Kaplan-Meier curves, volcano plots, heatmaps and correlation matrices
How to use Data Visualization
Before you begin: A signed-in SciExpert account
- 1
Open Data Visualization
From the workspace sidebar choose Data Visualization. On a phone, open the All menu and tap Data Visualization.
- 2
Set up your inputs
Charts and diagrams built to journal specification — correct sizing, typography and colour, exported at the resolution the publisher wants. Start with the smallest realistic input so you can check the output before scaling up.
- 3
Run it
Run the tool and check the first output: publication figures in r (ggplot2), python (matplotlib/seaborn) and graphpad prism.
- 4
Review what came back
Work through the results: custom colour palettes, typography and layouts matching journal guidelines; multi-panel figures with shared legends, highlighting and annotations; forest plots, kaplan-meier curves, volcano plots, heatmaps and correlation matrices.
- 5
Save or export
Use the save, copy or export options available in this service. Review the output before including it in a manuscript or sharing it with collaborators.