{"action":"created","issue":{"url":"https://api.github.com/repos/geneontology/pathways2GO/issues/51","repository_url":"https://api.github.com/repos/geneontology/pathways2GO","labels_url":"https://api.github.com/repos/geneontology/pathways2GO/issues/51/labels{/name}","comments_url":"https://api.github.com/repos/geneontology/pathways2GO/issues/51/comments","events_url":"https://api.github.com/repos/geneontology/pathways2GO/issues/51/events","html_url":"https://github.com/geneontology/pathways2GO/issues/51","id":410445731,"node_id":"MDU6SXNzdWU0MTA0NDU3MzE=","number":51,"title":"can a function occur in more than one place 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now, the converter adds all of the locations of all of the entities involved in a reaction as values on function occurs_in location statements.  \r\n\r\nThis is a change from the initial rule that occurs_in would only be asserted if all entity locations were equals.  The reason for the change is that, without it, the location information for cross-location reactions is completely lost in the conversion.  (It could be kept by adding entity located_in location statements into the models but that totally obscures the view in Noctua because of multi-level folding issues and is apparently not desirable from the standpoint of the GO-CAM domain model.)  \r\n\r\nSo, what should be do in the conversion for situations like this ?\r\n\r\n![screen shot 2019-02-14 at 11 02 49 am](https://user-images.githubusercontent.com/2086122/52810740-18997700-3048-11e9-9a0a-5e84ea6af5f7.png)\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/geneontology/pathways2GO/issues/comments/470273976","html_url":"https://github.com/geneontology/pathways2GO/issues/51#issuecomment-470273976","issue_url":"https://api.github.com/repos/geneontology/pathways2GO/issues/51","id":470273976,"node_id":"MDEyOklzc3VlQ29tbWVudDQ3MDI3Mzk3Ng==","user":{"login":"deustp01","id":12737623,"node_id":"MDQ6VXNlcjEyNzM3NjIz","avatar_url":"https://avatars2.githubusercontent.com/u/12737623?v=4","gravatar_id":"","url":"https://api.github.com/users/deustp01","html_url":"https://github.com/deustp01","followers_url":"https://api.github.com/users/deustp01/followers","following_url":"https://api.github.com/users/deustp01/following{/other_user}","gists_url":"https://api.github.com/users/deustp01/gists{/gist_id}","starred_url":"https://api.github.com/users/deustp01/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/deustp01/subscriptions","organizations_url":"https://api.github.com/users/deustp01/orgs","repos_url":"https://api.github.com/users/deustp01/repos","events_url":"https://api.github.com/users/deustp01/events{/privacy}","received_events_url":"https://api.github.com/users/deustp01/received_events","type":"User","site_admin":false},"created_at":"2019-03-06T20:58:56Z","updated_at":"2019-03-06T20:58:56Z","author_association":"COLLABORATOR","body":"We evade those long-distance transport issues by having a universe that consists of one cell surrounded_by extracellular space, so for that cholesterol transport case, we'd annotate the events that mobilize it and get it out of a peripheral cell, then annotate the events that get it taken up from extracellular space into a liver cell for further metabolism. The Reactome data model is unaware of that  \"peripheral\" - \"liver\" distinction so strictly the annotation says that intracellular cholesterol is mobilized and exported from the cell, then taken up by the cell and metabolized further. But if you look at a pathway where this is actually happening like [bile acid synthesis](https://reactome.org/PathwayBrowser/#/R-HSA-194068&SEL=R-HSA-192105&PATH=R-HSA-1430728,R-HSA-556833,R-HSA-8957322) you'll see that each reaction either occurs at a single location or moves stuff between two adjacent ones (though that depends on curator alertness; there's no rule to force that behavior). When you look at the pathway diagram on the Reactome website, you'll see that several separate cells have been laid out and cholesterol is mobilized in the one on the left, made extracellular, and taken up by the middle one that fills most of the diagram for conversion to bile acid. Those cells, however, are hand-drawn by the curator - the data model is unaware of them."}}
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