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Meta QSAR

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Presentation on using the Discovery Bus to develop a new field of research, "Meta QSAR" the comparative study of QSAR modelling methodology. Given at UK QSAR Society meeting at Syngenta October 22nd …

Presentation on using the Discovery Bus to develop a new field of research, "Meta QSAR" the comparative study of QSAR modelling methodology. Given at UK QSAR Society meeting at Syngenta October 22nd 2009

Published in: Health & Medicine, Technology

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Transcript

  • 1. Meta QSAR David Leahy
  • 2. Structures Data Descriptor Descriptor Descriptor Descriptor Test Set Filter Filter Filter Filter Model Model Model Model Transform Transform Train Train Predict Predict Predict Predict Predict Predict Predict Predict
  • 3. Calculate Descriptors Filter feature request ... Model build request ... Calculate descriptors request ... responses responses responses Planner Model Build Filter Features
  • 4. Calculate Descriptors Filter feature request ... Model build request ... Calculate descriptors request ... responses responses responses responses responses responses Planner Model Build Filter Features Calculate Descriptors
  • 5.  
  • 6. Meta QSAR. Methods
    • Wombat Database (thanks to Tudor)
      • First 80 data sets (human, n >75, Range > 2 Logs)
      • 7. Miscellaneous (HSA, Herg, CHI, Cl I )
    • Descriptors
      • CDK, CDL, MOPAC, HQSAR, E-State, H-State, LSER, AlogP, XlogP
    • Filter Feature
      • Hall method
    • Model Building (Continuous)
      • RNN, Rlinear, Rpart, RPLS, GUIDE
  • 8.  
  • 9. Model Assessment & Selection
    • Validity
      • Statistical tests
      • 10. y-scrambling
    • Stability
    • 11. Domain of Application
  • 12.  
  • 13.  
  • 14.  
  • 15.  
  • 16.  
  • 17.  
  • 18.  
  • 19. Meta QSAR: Automation of Decision Making in QSAR Modelling
  • 20. Mother of All QSAR Study
    • Expand data series
      • Wombat Database (~ 1000 datasets)
      • 21. EBI Stardrop Database (~2-3000 datasets)
      • 22. 0.5 million models, 25 years
    • Clouds
      • Amazon EC2
      • 23. 100 Microsoft Azure nodes
    • New methods
      • Simpler to add, any technology
  • 24. Amazon Master Server Amazon Worker Servers Azure Worker Servers Security Virtual Teams Inkspot Science Sci Software Services Workflow Cloud
  • 25. Inkspot Science Agents
  • 26. Inkspot Install to Azure
  • 27. Work in Progress
    • MOAQ Study
      • Classification Model Analysis
      • 28. Domain of applicability and local models
      • 29. Temporal QSAR
    • Open QSAR
      • MOAQ Results on-line
      • 30. New methods install and benchmark
      • 31. New data series
      • 32. Property prediction