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BigQuery_​SciWalker_​Exploration

Explore Scientific Data Stored on BigQuery using KNIME
Explore Life Sciences related data stored on BigQuery using KNIME Analytics PlatformThis workflow illustrates an example use case that can be relevant for life sciences research. It focuses on answering questions from the area of pharmaceutical research by linking differentdatasets stored in BigQuery and shows how scientific data can be explored interactively.Data: SciWalker Open Data is a comprehensive resource that contains chemistry related data like molecules, nucleotides and peptide sequences (overall 211 million unique molecules) that arelinked to additional scientific information. The datasets also include clinical and drug related data with links to different ontologies that allow us to compare data coming from different datasources using different wording is included.SciWalker Open Data can be found here: https://console.cloud.google.com/bigquery?p=sciwalker-open-dataThe data can be explored using the workflow mainly in 5 different steps where user actions are needed like selecting data in order to go to the next step:1) Type a disease into the autocomplete text field and select one2) Select one compound from the list3) Select a compound class from the bar chart4) Select a disease from the Word Cloud5) Explore the list of compounds that were tested for the diseases selected in 1) and 4)To open the views in the components press Ctrl+Double Click.A step by step guide describing how to connect to BigQuery using the DB Connector node can be found in the workflow description. Add credentials to the nodeconfiguration (seeinstructions in the workflowdescription) Step 1: Type a diseaseStep 3: Selecta compound classStep 2: Selectone compoundStep 5: Explore resultsStep 4: Select another disease from the Word Cloud Joiner DB Connector SelectCondition/Disease View CompoundClasses Extract Compounds& Tested Diseases Interactive View Joiner View overlap of testedcompounds for two diseases Get Data FromBigQuery Get more data View othertested diseases Explore Life Sciences related data stored on BigQuery using KNIME Analytics PlatformThis workflow illustrates an example use case that can be relevant for life sciences research. It focuses on answering questions from the area of pharmaceutical research by linking differentdatasets stored in BigQuery and shows how scientific data can be explored interactively.Data: SciWalker Open Data is a comprehensive resource that contains chemistry related data like molecules, nucleotides and peptide sequences (overall 211 million unique molecules) that arelinked to additional scientific information. The datasets also include clinical and drug related data with links to different ontologies that allow us to compare data coming from different datasources using different wording is included.SciWalker Open Data can be found here: https://console.cloud.google.com/bigquery?p=sciwalker-open-dataThe data can be explored using the workflow mainly in 5 different steps where user actions are needed like selecting data in order to go to the next step:1) Type a disease into the autocomplete text field and select one2) Select one compound from the list3) Select a compound class from the bar chart4) Select a disease from the Word Cloud5) Explore the list of compounds that were tested for the diseases selected in 1) and 4)To open the views in the components press Ctrl+Double Click.A step by step guide describing how to connect to BigQuery using the DB Connector node can be found in the workflow description. Add credentials to the nodeconfiguration (seeinstructions in the workflowdescription) Step 1: Type a diseaseStep 3: Selecta compound classStep 2: Selectone compoundStep 5: Explore resultsStep 4: Select another disease from the Word Cloud Joiner DB Connector SelectCondition/Disease View CompoundClasses Extract Compounds& Tested Diseases Interactive View Joiner View overlap of testedcompounds for two diseases Get Data FromBigQuery Get more data View othertested diseases

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