We developed a Bayesian hierarchical model to identify gene networks based on the similarity score generated from comparing the gene ontology fingerprints of gene pairs. Genes in this network were ...

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...

This is a preview. Log in through your library . Abstract In this article, we present a Bayesian hierarchical model for predicting a latent health state from longitudinal clinical measurements. Model ...

The ability to make adaptive decisions in uncertain environments is a fundamental characteristic of biological intelligence. Historically, computational ...

Understanding how and why animals use the environments where they occur is both foundational to behavioral ecology and essential to identify critical habitats for species conservation. However, some ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...

In the Big Data era, many scientific and engineering domains are producing massive data streams, with petabyte and exabyte scales becoming increasingly common. Besides the explosive growth in volume, ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

https://microcollaborative.atlassian.net/wiki/spaces/DSC/pages/13828181/Confronting+models+with+data In this working group we learn about methods and ideas for ...