Tutorial 4: Identifier Processing
Replace Compound/Enzyme IDs with Names
Please make sure, that the compound and enzyme databases are online, before performing the next steps. You may check this, with the command “Help/Database-Status”.
You may use the command “Nodes/Interpret Database-Identifiers”, to replace node labels with Names or with IDs. Click onto the buttons “>>>”, to change the direction, or to disable the processing of certain entry types (e.g. process only compounds or enzymes).
The checkbox “Increase node size” may be selected, to increase the size of enzyme and map nodes, to reflect the current or new label.
 
Replace Gene IDs with Enzyme IDs
Please make sure, that the KO database is online, before performing the next steps. You may check this, with the command “Help/Database-Status”.
You may use the command “Nodes/Interpret Database-Identifiers”, to replace labels from gene-nodes with enzyme IDs. Click onto the 4th change-button (KO/Gene ID) to change the text from “unchanged” to “>>>”. Click onto the other buttons until they show the“unchanged” setting.
By clicking “OK”, all nodes (or if a selection is made, only the selected nodes), will be evaluated as following: Only nodes with the node attribute “KEGG ID” (see Node tab) will be processed. If the ID contains identifiers, they are matched against the KO database entries and the KO database gene annotations. The EC annotation information from the relevant KO entries is extracted and used to rename the node. More than one EC number may correspond to the node gene or KO IDs.
This process works on KEGG KO-reference pathways as well on non-EST organism-specific pathways.
 
Another possibility for a similar result is to process KEGG Reaction IDs and using the corresponding EC annotation to label the graph nodes. This is possible, by not using the “KO/Gene ID” setting in the dialogue window, but by using the “Reaction No.” setting. This approach uses the KEGG SOAP API, to determine related EC annotations for the reaction IDs, connected to a particular graph node. The performance and versatility of these two approaches is not yet fully explored, so I can’t recommend which approach to choose at the moment.