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03_​Co-occurrence_​Network

Network of co-occuring Drug Names

This workflow describes the network creation process and specifically creates the drug-drug co-occurence network. Here, we use the Network Creator node to create 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 visual properties (color & shape) for the nodes within the network. These properties can be added by using the Feature Inserter node. After doing so, we use the Network Viewer JS (hidden in the View component) to visualize the network.

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 Creation of a co-occurence network of drug names tagged in documents. 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 Creation of a co-occurence network of drug names tagged in documents. 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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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: julian
Created at: 2019-01-18
On NodePit since: 2025-04-15
Last update: 2025-04-16
Created with KNIME version: v4.1.0
Tags: co-occurrence networksnetwork creatorvisualizationdrug predictionLife sciences

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