How Galactic can support causal searches

Ideal for: Understanding protein interactions, investigating biochemical and biological pathways, analysis of relationships between genes and proteins, determining the cause-and-effect relationship of compounds, deep diving into biological sequences (e.g. metabolic pathways, disease progression)


Biomedical literature contains a range of cause and effect relationships between genes, chemicals, diseases, processes and any target biological entity. Uncovering these relationships can provide valuable insights to strengthen and direct your research. To be able to capture these insights usually involves manually sifting through scientific articles to pick out the trends. Galactic provides a window into the connections in research areas through the causal interaction search function, which detects the interactions between concepts within text. These interactions can be causally or directly linked and include the detailed context of the relationship within the disease area.

The advanced natural language processing of Galactic detects all the relationships linked to your search term and categorises them providing you with an in-depth understanding of your search terms and their corresponding relationships. Galactic lists the relationship type by confidence interval to ensure accuracy and precision when conducting your analysis.

How–to : conduct a causal search

The unique causal search analysis captures relationships across terms including: chemicals, proteins, genes, cells, phenotypes, and diseases. Run the search using your two selected search terms to uncover the types of the interactions and the corresponding articles for each relationship. Use the ‘refine by’ functionality to search contextually across causal interactions and explore around your search terms further.

Conducting a causal search allows you to have a comprehensive view of the interactions related to your research area and to drill down into specific relationships that you may not have sought out in manual research. For example, you may know that a protein is involved in a particular interaction, running a causal search can identify examples of this interaction in literature and provide context.

Galactic ensures the search results are accurate and exhaustive by including popular ontologies and vocabularies, such as HGNC and MeSH, as well as those curated by Biorelate for added precision. Articles are ingested by Galactic upon publication, ensuring causal searches are extensive and up to date. Users can license the entire causal database or sections of it for internal analysis by contacting sales and support at

To find out how to conduct a causal search and enhance your data analysis click on the video below.

Impact & Benefit


Galactic auto-curates causal interactions from literature to provide data that is present in no other database.


Galactic processes new articles in real time ensuring that the most recent publications are included in the causal search. The alert function enables you to keep up to date and notified of any new publications relevant to your search.


Providing insights and interactions in an easy to navigate format that would otherwise only be sought out manually saves you time and allows you to efficiently re-allocate time to further data analysis or essential project work.


Filtering the search by confidence level and being able to add context using the ‘refine by’ feature allows you to customise your search to a specific therapeutic area.

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