Verification of Three-Phase Dependency Analysis Bayesian Network Learning Method for Maize Carotenoid Gene Mining.

ABSTRACT:

Background and objective

Mining the genes related to maize carotenoid components is important to improve the carotenoid content and the quality of maize.

Methods

On the basis of using the entropy estimation method with Gaussian kernel probability density estimator, we use the three-phase dependency analysis (TPDA) Bayesian network structure learning method to construct the network of maize gene and carotenoid components traits.

Results

In the case of using two discretization methods and setting different discretization values, we compare the learning effect and efficiency of 10 kinds of Bayesian network structure learning methods. The method is verified and analyzed on the maize dataset of global germplasm collection with 527 elite inbred lines.

Conclusions

The

SUBMITTER: Liu J 

PROVIDER: S-EPMC5554554 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature