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04.1. Integrated Deployment - solution

Integrated Deployment Solution

Solution to the "Integrated Deployment" exercise for the advanced Life Science User Training
- capture the data preprocessing
- capture the model prediction
- deploy the captured workflow

Activity I: Create Model for Deployment - capture the preprocessing of your data and the model prediction using the Capture Workflow Start and Capture Workflow End nodes - combine your captured workflows using the Workflow Combiner - write/deploy your workflow using the Workflow Writer node Integrated DeploymentThis workflow demonstrates integrated deployment for a Random Forest Model for a bioactivity data set using binary fingerprints.The data set represents a subset of 844 compounds evaluated for activity against CDPK1. 181 compounds inhibited CDPK1 with IC50 below 1uM and have "active" as their class.More information is available https://www.ebi.ac.uk/chemblntd/#tcams_dataset. See Set 19. Step 1: Capture Preprocessing- use the Capture Workflow Start node withdata port types to start capturing yourpreprocessing part of the workflow- use the RDKit Fingerprint node to createbinary fingerprints. - use the Capture Workflow End node withdata port types to end your preprocessing partof the workflow Step 2: Capture Prediction Model- use the Capture Workflow Start node with data port typesto start capturing your prediction model- use the Random Forest Predictor node for your modelpredictions- use the Column Filter node to remove your binaryfingerprint column - use the Capture Workflow End node with data port typesto end your prediction model Step 3: Combine capturedWorkflows and Deploy- use the Workflow Combinernode to combine thepreprocessing workflow and themodel prediction workflow (HINT:the first part needs to beconnected to the upper inputport)- use the Workflow Writer nodeto deploy your workflow TCAMS_CDPK1_subset_ML.tableNode 348Node 349 Partitioning Random ForestLearner Random ForestPredictor RDKit Fingerprint Scorer (JavaScript) CaptureWorkflow Start CaptureWorkflow End Workflow Combiner CaptureWorkflow End CaptureWorkflow Start Column Filter Workflow Writer Table Reader Table Reader CaptureWorkflow End Activity I: Create Model for Deployment - capture the preprocessing of your data and the model prediction using the Capture Workflow Start and Capture Workflow End nodes - combine your captured workflows using the Workflow Combiner - write/deploy your workflow using the Workflow Writer node Integrated DeploymentThis workflow demonstrates integrated deployment for a Random Forest Model for a bioactivity data set using binary fingerprints.The data set represents a subset of 844 compounds evaluated for activity against CDPK1. 181 compounds inhibited CDPK1 with IC50 below 1uM and have "active" as their class.More information is available https://www.ebi.ac.uk/chemblntd/#tcams_dataset. See Set 19. Step 1: Capture Preprocessing- use the Capture Workflow Start node withdata port types to start capturing yourpreprocessing part of the workflow- use the RDKit Fingerprint node to createbinary fingerprints. - use the Capture Workflow End node withdata port types to end your preprocessing partof the workflow Step 2: Capture Prediction Model- use the Capture Workflow Start node with data port typesto start capturing your prediction model- use the Random Forest Predictor node for your modelpredictions- use the Column Filter node to remove your binaryfingerprint column - use the Capture Workflow End node with data port typesto end your prediction model Step 3: Combine capturedWorkflows and Deploy- use the Workflow Combinernode to combine thepreprocessing workflow and themodel prediction workflow (HINT:the first part needs to beconnected to the upper inputport)- use the Workflow Writer nodeto deploy your workflow TCAMS_CDPK1_subset_ML.tableNode 348Node 349 Partitioning Random ForestLearner Random ForestPredictor RDKit Fingerprint Scorer (JavaScript) CaptureWorkflow Start CaptureWorkflow End Workflow Combiner CaptureWorkflow End CaptureWorkflow Start Column Filter Workflow Writer Table Reader Table Reader CaptureWorkflow End

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

Download Workflow
On NodePit since: 2022-05-17
Last update: 2024-04-26
Created with KNIME version: v4.5.2
Tags: machine learningeducationlife scienceintegrated deployment

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