Euretos Relation Map



Visualized molecular and biological data-based relations

The Relation Map visualises relations which originate from databases and that are often difficult to access or ‘read’ such as molecular interactions, expression values and human annotations. Visualised as relation maps, this enables unique, data driven insights such as term clustering, indirect associations and term centrality.

Low-bias, data driven analysis
Rapid overview of full context
Discover indirect interactions
1-click cluster analysis of data sets
Relation Map

The world's largest AI-integrated knowledge base

We use AI to recognise and find relevant information for molecular disease and drug research. Information from over 275 life sciences databases and millions of publications and patents is harmonised and integrated. This provides a unique backdrop for powerful data-based analysis.
Relation Map

A unique visual analysis of data-based  knowledge

With the Relation map over 180 relation types (e.g. inhibits) and their measures (e.g. IC50 = 1.2) connect over 8 million biological terms. Many of the relations are of a molecular nature such as protein-protein interaction or tissue and cell type expression. Also, human annotations are included which for instance link genes to pathways, phenotypes and diseases.
Enabling world leading pharma, biotech and academic institutions
Janssen and Janssen Pharmaceutical Companies
Leiden Academic Centre for Drug Research
Astra Zeneca
Boehringer Ingelheim
Tufts University
Relation Map

Review associations at a glance

You can add terms to the relation map and immediately see the types relations they have with all other terms. If two terms have multiple relations, a circle with the number of relations is shown. Evaluate the connections of any term in seconds!
Relation Map

Access to combined evidence from databases and literature

For any relation in the Relation Map, all evidence is available at a single click. All sources are shown including relevant measures (e.g. IC50 value for an 'inhibits' relation). All literature that mentions the concepts in the relation are also show, giving a complete overview of all available evidence!
Relation Map

Discover intermediate associations

When you select two terms, related or not, you can find terms that are related to both. These intermediate associations are nearly impossible to find without the networked visualization of the Relation Map. Especially terms which have no direct association can suddenly turn out to have many relevant shared connections that provide new, unexpected insights.
Relation Map

Quickly identify related clusters in your data

When you drop a set of terms in a relation map you can immediately see how they are connected. Clusters in your data are identified immediately and can be saved as sub-sets for export or further analysis in Analytics.
Enabling world leading pharma, biotech and academic institutions
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Transforming Disease and Drug Research

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