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1
Intro
2
Modeling Missing Data
3
Data Characteristics
4
Variable Presence
5
Association
6
Ensemble
7
Bone Regeneration
Description:
Explore multiomics data analysis and modeling techniques in this 28-minute presentation from Wolfram. Learn about the challenges of analyzing ill-conditioned biological data sets with many variables and few records. Discover how ParetoGP develops simple algebraic models using evolutionary search to reward simplicity and accuracy. Gain insights on key variables, associations, and combinations while generating concise, explainable models. Follow the demonstration of the DataModeler applied to cancer therapeutics and bone regeneration data sets. Cover topics including modeling missing data, data characteristics, variable presence, association, ensemble modeling, and bone regeneration applications.

Biological Data Insight and Modeling with ParetoGP for Multiomics Analysis

Wolfram
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