db-reactome

Pathway enrichment analysis on a gene list is performed by querying the Reactome Analysis Service to identify statistically significant biological pathways. This process maps your genes to known molecular interactions and returns enriched pathways with associated statistical significance.

Overrepresentation analysis in systems biology identifies which biological pathways are statistically overrepresented in a given gene or protein list. It helps researchers understand which molecular interactions and biological processes are most significantly affected in their experimental dataset.

Gene expression datasets can be analyzed to uncover relevant biological pathways using the Reactome Analysis Service. The analysis processes your expression data to identify significantly impacted pathways and molecular interactions within the biological system.

Detailed biological pathway data and molecular interactions are retrieved by querying the Reactome Content Service REST API. This provides direct access to comprehensive information about specific pathways, reactions, and molecular entities for systems biology studies.

Querying the Reactome REST API does not strictly require a Python client library, as the REST API can be accessed directly. However, an optional Python client library is supported to simplify data retrieval and computational analysis tasks.

The best way to map a gene list to biological pathways is by utilizing a dedicated Reactome analysis tool for gene-pathway mapping. This approach processes your gene list to identify enriched pathways and molecular interactions with statistical significance.