About: Time Series Adjustment Enhancement of Hierarchical Modeling of Arabidopsis Thaliana Gene Interactions

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Time Series Adjustment Enhancement of Hierarchical Modeling of Arabidopsis Thaliana Gene Interactions
Creator	Wu, Bo Farrell, John John, David Allen, Edward Harkey, Alexandria »more»
source	PMC
abstract	Network models of gene interactions, using time course gene transcript abundance data, are computationally created using a genetic algorithm designed to incorporate hierarchical Bayesian methods with time series adjustments. The posterior probabilities of interaction between pairs of genes are based on likelihoods of directed acyclic graphs. This algorithm is applied to transcript abundance data collected from Arabidopsis thaliana genes. This study extends the underlying statistical and mathematical theory of the Norris-Patton likelihood by including time series adjustments.
has issue date	2020-02-01(xsd:dateTime)
bibo:doi	10.1007/978-3-030-42266-0_11
has license	no-cc
sha1sum (hex)	ac1d1a76a5c769b1b6a526983606a533f90c803d
schema:url	https://doi.org/10.1007/978-3-030-42266-0_11
resource representing a document's title	Time Series Adjustment Enhancement of Hierarchical Modeling of Arabidopsis Thaliana Gene Interactions
has PubMed Central identifier	PMC7197098
schema:publication	Algorithms for Computational Biology
resource representing a document's body	covid:ac1d1a76a5c769b1b6a526983606a533f90c803d#body_text
is schema:about of	named entity 'study' named entity 'Arabidopsis' named entity 'GENE' named entity 'GENES' named entity 'HIERARCHICAL' »more»

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