Dive into the cutting-edge world of biomedical research with our latest blog post on “OntoloViz: a GUI for interactive visualization of ranked disease or drug lists using the MeSH and ATC ontologies,” and discover how this innovative tool is revolutionizing the way scientists visualize and analyze complex data.
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OntoloViz: a GUI for interactive visualization of ranked disease or drug lists using the MeSH and ATC ontologies.
Ley et al., Bioinform Adv 2023
<!– DOI: 10.1093/bioadv/vbad113 //–>
https://doi.org/10.1093/bioadv/vbad113
The development of OntoloViz, a new tool designed to visualize drugs and diseases within the Medical Subject Headings (MeSH) and Anatomical Therapeutic Chemical (ATC) ontologies, offers a significant advancement in the field of biomedical informatics. Unlike existing methods that require extensive programming knowledge, OntoloViz provides a Graphical User Interface (GUI) that simplifies the creation of sunburst layout visualizations. This tool is particularly useful for displaying hierarchical relationships and frequencies of terms within these structured vocabularies.
OntoloViz stands out by requiring only a list of disease or drug names as input, with the option to include numerical parameters for a more detailed analysis. It supports the exploration of gene and drug lists by allowing values to be aggregated in the ontology tree structure. The utility of OntoloViz is demonstrated through two use cases: visualizing drugs tested for COVID-19 using the ATC Classification and mapping human diseases in the MeSH ontology.
This tool is accessible for download from PyPi, with its source code, test data, templates, and documentation available on GitHub (https://github.com/Delta4AI/OntoloViz). OntoloViz’s ease of use and intuitive visual outputs make it an important resource for researchers looking to contextualize diseases and drugs without the need for complex programming skills.