Learning a Probabilistic Boolean Network model from biological pathways and time-series expression data

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Vardaan PahujaPabitra Mitra

Abstract

The problem of inferring a stochastic model for gene regulatory networks is addressed here. The prior biological data includes biological pathways and time-series expression data. We propose a novel algorithm to use both of these data to construct a Probabilistic Boolean Network (PBN) which models the observed dynamics of genes with a high degree of precision. Our algorithm constructs a pathway tree and uses the time-series expression data to select an optimal level of tree, whose nodes are used to infer the PBN.

Related Concepts

Biochemical Pathway
Genes
Trees (plant)
phenyl-N-tert-butylnitrone
Gene Regulatory Networks
Two-Parameter Models
Anatomic Node
Boolean
Gene Modules
Protein Expression

Related Feeds

Brain-Computer Interface

A brain-computer interface, also known as a brain-machine interface, is a bi-directional communication pathway between an external device and a wired brain. Here is the latest research on this topic.

© 2020 Meta ULC. All rights reserved