Document Type

Presentation

Publication Date

3-5-2009

Subjects

Graphical modeling (Statistics), System theory, Information theory, Machine learning -- Statistical methods, Bayesian statistical decision theory, Epistasis (Genetics)

Abstract

This talk explains reconstructability analysis (RA), a graphical modeling methodology based in information theory & graph theory which overlaps more familiar machine learning & statistical methods such as log-linear models & Bayesian networks. The talk reports on the use of RA in a recent bioinformatics study of human gene (SNP) - disease (diabetes) association & epistasis & in some other biomedical applications of RA.

Keywords: Reconstructability Analysis, biomedical research, bioinformatics, categorical data, multivariate statistics, exploratory modeling, confirmatory modeling

Rights

© The Author

Description

Presentation at Oregon Health Sciences University, March 5, 2009. A very similar presentation was given at the Systems Sciences seminar on Feb 15, 2009, and before that at the University of Chicago Department of Human Genetics on Jan 16, 2009.

Persistent Identifier

https://archives.pdx.edu/ds/psu/42804

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