Meta QSAR
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share

Meta QSAR

  • 1,781 views
Uploaded on

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

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
1,781
On Slideshare
1,778
From Embeds
3
Number of Embeds
2

Actions

Shares
Downloads
23
Comments
0
Likes
0

Embeds 3

http://www.linkedin.com 2
http://www.slideshare.net 1

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

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