This guide will take approximately 10 minutes to complete.
What is Causaly Target Ontology?
Causaly Targets is a custom ontology curated and maintained by Causaly, enabling our users to perform target-related searches more rapidly and effectively.
The current version of Causaly Target Ontology consists of 38,930 targets, updated monthly.
It has the following key features and benefits:
- Saves time – All relevant target-related UMLS categories are selected with a single click, whether they are proteins, genes, or molecular functions.
- Increases sensitivity – Insights are synthesized from all aggregated target concepts, making sure that you don’t miss any critical evidence.
- Reduces noise – Targets are grouped into target families and specific targets to give you a more focused view.
- Better precision – Explore a specific functional target class to finetune your results for optimal precision and relevance.
Target discovery using the Causaly Targets filter
The Causaly Targets ontology accelerates screening in target discovery and validation, biomarker discovery, and translational research use cases. The ontology is selected by default for all target and biomarker related searches in the platform.
Use Case: Targets for glioblastoma
To explore this use case in Causaly, use Intelligent Search to find targets for glioblastoma (link).
In the results page, the pre-selected filters include both “specific targets” and “generic targets” within the Causaly Targets filter (Figure 1).
Figure 1: Within the Causaly Targets filter, “specific target” and “generic target” have been pre-selected.
With these filters selected, the dendrogram view will categorize the targets based on whether they are specific targets (“specific”) or target families (“generic”).
Scroll through the dendrogram to explore the specific targets (Figure 2) and target families (Figure 3) for glioblastoma. You can further refine the results to focus on just one of the categories.
Figure 2: The category “specific targets” within the dendrogram view.
Figure 3: The category “generic targets” within the dendrogram view.
TIP! Results in “specific targets” have been aggregated for genes, proteins, alleles and gene products, receptors, and signaling pathways. For example, concepts across different categories are aggregated under “MTOR”, which is related to glioblastoma in the literature, as illustrated in Figure 4.
Figure 4: Aggregation of relevant target concepts under “MTOR”.
Under specific targets, you can further finetune the results using the Target Class categories (Figure 5). As part of Causaly’s custom target ontology, the Target Classes filters have been designed to give greater clarity on the types of targets that can influence a biomedical concept. You can examine your results based on protein functions so that you can make more informed decisions. Visit this link to find out more about the Target Classes filters.
Figure 5: Refine to a protein class using the Target Classes filter under “specific targets”.
Explore/validate targets in Intelligent Search
Learn about the roles and effects of your target of interest by performing a target search. Causaly’s Target Ontology gives you the option to include all relevant target concepts so you can quickly uncover supporting evidence in the literature with better coverage and reduced noise.
Use Case: Validate target-disease association between BRCA2 and Colorectal Cancer
To explore this use case in Causaly, use Intelligent Search to investigate the relationship between BRCA2 and colorectal cancer (link). Causaly detects BRCA2 in its Target Ontology and returns the matching target with all relevant UMLS terms aggregated (Figure 6).
Figure 6: Causaly Targets aggregates the relevant UMLS terms under “BRCA2”.
Any direct relationships between BRCA2 and colorectal cancer found in the literature are presented in the results, including those describing different molecular forms and conditions of BRCA2 (Figure 7). This functionality ensures that you don’t miss any critical insights and validates gene-disease associations with additional, related information.
Figure 7: Colorectal carcinoma is associated with multiple concepts under “BRCA2”.
TIP! To see the UMLS terms covered by ‘BRCA2’ in the search, click on the down arrow next to ‘BRCA2’ and view related concepts (Figure 8). Examine the narrower and related concepts of BRCA2 automatically included to increase sensitivity.
Figure 8: Click on the down arrow within the concept to view related concepts.
You can exclude specific concepts in this view to reduce noise in the search. Simply click on the checkbox to de-select the concept (Figure 9).
Figure 9: Narrower concepts of ‘BRCA2’ from the UMLS ontologies.
If you already have a specific concept in mind, you can search directly with the UMLS concept for highly specific results. Simply select one of the concepts aggregated under a target, or directly enter the UMLS concept into the search field. For example, search for the association between “egfr exon 20 mutation” (Figure 10) and NSCLC (link).
Figure 10: Use a specific UMLS concept for a more restricted, focused search.