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PIPELINE PILOT

Empower your research team with a flexible scientific platform that drives efficiency, collaboration and innovation.

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Modeling Component Collection for Pipeline Pilot

The Modeling Collection offers a comprehensive set of learning and data modeling capabilities, statistical filters, and clustering components optimized for large real-world data sets. This collection of components extends Pipeline Pilot's standard capabilities to include statistics and predictive modeling for data mining applications.

Create protocols with powerful methods such as:

  • Fast data clustering
  • Unsupervised categorical learning using Bayesian Statistics
  • Principal component analysis
  • Linear regression and partial least squares regression

The modeling methods provide built-in methods, such as various cross-validation techniques, to ensure the quality of the models built. They also provide methods to assess the quality of each prediction as the model is subsequently applied. This is particularly important as models are increasingly deployed to end-users who may not be familiar with the training data or limits of the modeling method.

When combined with the separately available Chemistry Collection, you can perform:

  • Structure activity modeling
  • Compound clustering
  • Maximal common substructure search

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