Quantifying gene relatedness via nonlinear prediction of gene

Details Quantifying gene relatedness via nonlinear prediction of gene Quantifying gene relatedness via nonlinear prediction of gene

2006-02-21

2006-02-21

Moran, Marjorie A. (Department: 2857)

Data processing: measuring, calibrating, or testing

Measurement system in a specific environment

Biological or biochemical

C702S020000, C706S015000, C706S021000, C435S006120

Reexamination Certificate

active

07003403

ABSTRACT:
Relatedness between genes is quantified by constructing nonlinear models predicting gene expression. Effectiveness of the model is evaluated to provide a measurement of the relatedness of genes associated with the model. Various types of models, including full-logic or neural networks can be constructed. A graphical user interface presents results of the analysis to allow evaluation by a user. Each gene's contribution to the measurement of relatedness can be shown on a graph, and graphical representations of models used to predict gene expression can be displayed.

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