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03_​Co-occurrence_​Network

Workflow

Co-occurrence Network
co-occurrence networksnetwork creatorvisualizationdrug predictionlife science
Creating the Term Co-occurrence table. Combine newly found entities and known entities. 1) Filter co-occurrences2) Join ATC codes and Origin information Create the drug-drug co-occurrence network Retrieve semantic relations between newly identified drug names anddrug names from the initial list Co-occurence NetworkThis workflow describes the network creation process and specifically creates the drug-drug co-occurence network. Here, we use the Network Creator node tocreate an empty network that can be filled with new nodes and edges by using the Object Inserter. Afterwards, we predict the ATC codes and create visualproperties (color & shape) for the nodes within the network. These properties can be added by using the Feature Inserter node. After doing so, we use theNetwork Viewer JS (hidden in the View component) to visualize the network. Insert nodesand edgesCountco-occurrencesAdding colorsAdding shapeCreate EdgeIDPort 1: New drugs with relationsPort 2: New drugs without relationBag of words ofunique set of (test)documentsExtracted entities fromtest setDrug names andATC CodesWords used for training(case insensitive)Write network todata folderWrite new drugs without relationto data folderWrite node propertiesto data folder Network Creator Object Inserter Term Co-OccurrenceCounter Feature Inserter Feature Inserter Prepare drug namesfor network Filterco-occurrences ATC Prediction Visual Properties String Manipulation Get name relations Table Reader Table Reader Table Reader Table Reader Network Writer Table Writer Table Writer Random subgraph View Creating the Term Co-occurrence table. Combine newly found entities and known entities. 1) Filter co-occurrences2) Join ATC codes and Origin information Create the drug-drug co-occurrence network Retrieve semantic relations between newly identified drug names anddrug names from the initial list Co-occurence NetworkThis workflow describes the network creation process and specifically creates the drug-drug co-occurence network. Here, we use the Network Creator node tocreate an empty network that can be filled with new nodes and edges by using the Object Inserter. Afterwards, we predict the ATC codes and create visualproperties (color & shape) for the nodes within the network. These properties can be added by using the Feature Inserter node. After doing so, we use theNetwork Viewer JS (hidden in the View component) to visualize the network. Insert nodesand edgesCountco-occurrencesAdding colorsAdding shapeCreate EdgeIDPort 1: New drugs with relationsPort 2: New drugs without relationBag of words ofunique set of (test)documentsExtracted entities fromtest setDrug names andATC CodesWords used for training(case insensitive)Write network todata folderWrite new drugs without relationto data folderWrite node propertiesto data folder Network Creator Object Inserter Term Co-OccurrenceCounter Feature Inserter Feature Inserter Prepare drug namesfor network Filterco-occurrences ATC Prediction Visual Properties String Manipulation Get name relations Table Reader Table Reader Table Reader Table Reader Network Writer Table Writer Table Writer Random subgraph View

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Nodes

03_​Co-occurrence_​Network consists of the following 149 nodes(s):

Plugins

03_​Co-occurrence_​Network contains nodes provided by the following 8 plugin(s):