New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data-Reference-Cited by-同舟云学术

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New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data

Published:2017-04 Issue:4 Volume:24 Page:340-356
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Gogoshin Grigoriy¹,Boerwinkle Eric²³,Rodin Andrei S.¹

Affiliation:

1. Diabetes and Metabolism Research Institute, City of Hope, Duarte, California.

2. Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas.

3. Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/cmb.2016.0100

Reference53 articles.

1. Inference of regulatory networks with a convergence improved MCMC sampler

2. A new look at the statistical model identification

3. THE ATHEROSCLEROSIS RISK IN COMMUNIT (ARIC) STUDY: DESIGN AND OBJECTIVES

4. The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks

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