Icon

BigQuery SciWalker Exploration

Explore Scientific Data Stored on BigQuery using KNIME

This example shows how KNIME Analytics Platform can be used to explore and analyze data stored in Google BigQuery.

Data used for the example workflow:
SciWalker Open Data is a comprehensive resource that contains chemistry related data like molecules, nucleotides and peptide sequences (overall 211 million unique molecules) that are linked to additional scientific information. The datasets also include clinical and drug related data with links to different ontologies, which allow us to compare data coming from different data sources using different wording is included.

The data can be explored using the workflow following 5 main steps where user action is needed like selecting data in order to go to the next step:
Step 1) Type a disease into the autocomplete text field and select one
Step 2) Select one compound from the list
Step 3) Select a compound class from the bar chart
Step 4) Select a disease from the Word Cloud
Step 5) Explore the list of compounds that were tested for the diseases selected in 1) and 4)

To open the interactive views, right click the component and select "Execute & Open Views" or select Interactive View if component is already executed.

Note: you will need Google BigQuery credentials to run this workflow.

This 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 different datasets storedin BigQuery and shows how scientific data can be explored interactively. Step 1: Type a diseaseStep 3: Selecta compound classStep 2: Selectone compoundStep 5: Explore resultsStep 4: Select another disease from the Word Cloud Joiner SelectCondition/Disease View CompoundClasses Extract Compounds& Tested Diseases View Compounds andClinical Studies Joiner View overlap of testedcompounds for two diseases Get Data FromBigQuery Get more data View othertested diseases Google BigQueryConnector This 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 different datasets storedin BigQuery and shows how scientific data can be explored interactively. Step 1: Type a diseaseStep 3: Selecta compound classStep 2: Selectone compoundStep 5: Explore resultsStep 4: Select another disease from the Word Cloud Joiner SelectCondition/Disease View CompoundClasses Extract Compounds& Tested Diseases View Compounds andClinical Studies Joiner View overlap of testedcompounds for two diseases Get Data FromBigQuery Get more data View othertested diseases Google BigQueryConnector

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Martyna
Created at: 2019-05-17
On NodePit since: 2025-04-15
Last update: 2025-04-16
Created with KNIME version: v4.1.2
Tags: BigQuerySciWalkerclinical trialclinical studydisease

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!