NodeExpand Bit Vector

Manipulator

This node splits the Bit Vector to integer columns.

The Bit Vector Generator node generates some position and name information as metadata. You can use that information in this node.

Input ports
  1. Data with Bit Vector Type: Data
    Table containing at least one bit vector column.
Output ports
  1. Data table Type: Data
    Table with generated columns.
  1. Validating KNIME Workflows
    reproducibility validation testing XGBoost RDKit
    This workflow demonstrates how to take a standard KNIME workflow and adapt it to be deployable as a web service using th…
    knime > Examples > 50_Applications > 51_Model_Deployment_and_Validation > 01_Deploying_and_Validating_models_as_WebServices
  2. TeachOpenCADD Workflow 7: Ligand-based screening: Machine learning
    Ligand-based screening Machine learning Random forest Support vector machine Artificial neural networks
    With the continuously increasing amount of available data, machine learning (ML) gained momentum in drug discovery and e…
    volkamerlab > Public > TeachOpenCADD_Workflow7_Machine_learning > TeachOpenCADD_Workflow7_Machine_learning
  3. Model Optimization and Selection
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementat…
    knime > Examples > 04_Analytics > 11_Optimization > 08_Model_Optimization_and_Selection
  4. Generate ChEMBL Predictions
    There has been no description set for this workflow's metadata.
    greglandrum > Public > In progress > ONNX > Generate ChEMBL Predictions
  5. 03_Bioactivity_Prediction_Learn_All_Methods
    This workflow is used for learning the model. It deploys a complex parameter optimzation protocol for model building whe…
    knime > Examples > 50_Applications > 37_Monster_Model_Factory > Process > _Process_Step_Templates > workflows > Templates > 03_Bioactivity_Prediction_Learn_All_Methods
  6. TeachOpenCADD - a teaching platform for computer-aided drug design using KNIME
    ChEMBL query PDB query Molecular filtering Unwanted substructures Lipinski's rule of five Similarity search Compound clustering Maximum common substructure Machine learning
    The TeachOpenCADD KNIME pipeline consists of eight inter-connected workflows (W1-8) , each containing one topic in compu…
    volkamerlab > Public > TeachOpenCADD > TeachOpenCADD
  7. 03_Bioactivity_Prediction_Learn_Testing
    parameter optimization loop machine learning
    This workflow is used for learning the model. It deploys a simple version of parameter optimzation protocol designed for…
    knime > Examples > 50_Applications > 37_Monster_Model_Factory > Process > _Process_Step_Templates > workflows > Templates > 03_Bioactivity_Prediction_Learn_Testing