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Bioactivity
Chemistry Cheminformatics Integrated deployment Life science Logistic regression Machine learning Molecular fingerprints Naive bayes Parameter optimization
  1. Workflow
    Machine Learning Chemistry
    Life Sciences Cheminformatics Machine Learning
    +1
    This workflow snippet demonstrates how to train a bioactivity model using chemical structures. From the chemical structure we gen…
    knime > Workflow Snippets > Machine Learning Chemistry
    1
    knime
  2. Workflow
    Extract SMILES or other data from ChEMBL
    Giribio Nyroindia Chembl
    +5
    Pull any data (SMILES, Activity, Assay, others from ChEMBL via API GET services) Input: CSV or List of ChEMBL ID (Target or Molec…
    nyroindia > Workshops by Girinath (@giribio) on CADD > GGP2113_ChEMBLSMILES
    1
    nyroindia
  3. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Life Sciences > Events > 2020_10_Integrated_Deployment_In_Action_Webinar > Model Selection with Integrated Deployment
    1
    knime
  4. Workflow
    04_Generate_Features
    Apache Spark KNIME Workflow Executor for Apache Spark KWEfAS
    +4
    This is the forth workflow in the PubChem Big Data story.
    knime > Life Sciences > Cheminformatics > ChemistryFPs_vs_BiologyFPs > DataPrep > 04_Generate_Features
    0
    knime
  5. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Education > Courses > L4-CA Machine Learning for Chemical Applications > Exercises > 02_Hyperparameter Optimization
    0
    knime
  6. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Education > Courses > L4-CA Machine Learning for Chemical Applications > Solutions > 02_Hyperparameter Optimization_Bonus
    0
    knime
  7. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    knime > Education > Courses > L4-CA Machine Learning for Chemical Applications > Solutions > 02_Hyperparameter Optimization
    0
    knime
  8. Workflow
    Machine Learning Chemistry
    Life Sciences Cheminformatics Machine Learning
    +1
    This workflow snippet demonstrates how to train a bioactivity model using chemical structures. From the chemical structure we gen…
    hiroaki_shiraishi > Public > Machine Learning Chemistry
    0
    hiroaki_shiraishi
  9. Workflow
    Model Prediction Chemistry
    Life Sciences Cheminformatics Bioactivity
    +1
    This workflow snippet demonstrates how to use a trained bioactivity model to predict the bioactivity of new molecules. The model …
    knime > Workflow Snippets > Model Prediction Chemistry
    0
    knime
  10. Workflow
    Model Selection with Integrated Deployment
    Chemistry Naive bayes Random forest
    +11
    This workflow deploys an advanced parameter optimzation protocol with four machine learning methods. In this implementation the c…
    janina > Public > 2022_01_KNIME_User_Day > Model Selection with Integrated Deployment
    0
    janina