<p>Only significant links are presented, and grey lines indicating links with no sign was detected. Grey and black circles represent species with a Quaternary and Tertiary syndrome respectively. White circles are either environmental variables (mean temperature in the warmest quarter of the year (Twarm), annual precipitation (anualP), soil types (soil), land use (landuse), orientation (orientation), dominant form (dom_form) and spatial location (spac)) or species with no syndrome associated. Continuous and dashed lines represent negative and positive associations respectively. Complete names for species are provided in the appendix and environmental variable categories in the methods section.</p
<p>A Bayesian network is a machine learning tool for organizing and encoding statistical dependence ...
This phylogeny was estimated using MCMC_SEQ, from data simulated based on the true species network. ...
Understanding what determines species' geographic distributions is crucial for assessing global chan...
<p>Nodes in grey are informed by empirical data; nodes in white are elicited from experts. The nodes...
In today's world, it is becoming increasingly important to have the tools to understand, and ultimat...
Every circular node represents a biological element in the drought signaling pathway. Every edge or ...
Abstract: There are different structure of the network and the variables, and the process of learnin...
We review the applicability of Bayesian networks (BNs) for discovering relations between genes, envi...
Understanding functional relationships within ecological networks can help reveal keys to ecosystem ...
(A) BN for controls (healthy individuals). (B) BN for IPF patients. Nodes represent specific cell ty...
Motivation: Reverse engineering GI networks from experimental data is a challenging task due to the ...
The main objective of this research is to connect Social Network Analysis descriptive measures of ce...
<p>The confidences of the edges are represented as percentage of the edges that persisted across 20...
The gray filled circle means the observed data, the green border dots to represent a fixed parameter...
Top left: NBC = Naïve Bayes classifier; top right: TAN = Tree augmented Naïve-Bayes network; bottom ...
<p>A Bayesian network is a machine learning tool for organizing and encoding statistical dependence ...
This phylogeny was estimated using MCMC_SEQ, from data simulated based on the true species network. ...
Understanding what determines species' geographic distributions is crucial for assessing global chan...
<p>Nodes in grey are informed by empirical data; nodes in white are elicited from experts. The nodes...
In today's world, it is becoming increasingly important to have the tools to understand, and ultimat...
Every circular node represents a biological element in the drought signaling pathway. Every edge or ...
Abstract: There are different structure of the network and the variables, and the process of learnin...
We review the applicability of Bayesian networks (BNs) for discovering relations between genes, envi...
Understanding functional relationships within ecological networks can help reveal keys to ecosystem ...
(A) BN for controls (healthy individuals). (B) BN for IPF patients. Nodes represent specific cell ty...
Motivation: Reverse engineering GI networks from experimental data is a challenging task due to the ...
The main objective of this research is to connect Social Network Analysis descriptive measures of ce...
<p>The confidences of the edges are represented as percentage of the edges that persisted across 20...
The gray filled circle means the observed data, the green border dots to represent a fixed parameter...
Top left: NBC = Naïve Bayes classifier; top right: TAN = Tree augmented Naïve-Bayes network; bottom ...
<p>A Bayesian network is a machine learning tool for organizing and encoding statistical dependence ...
This phylogeny was estimated using MCMC_SEQ, from data simulated based on the true species network. ...
Understanding what determines species' geographic distributions is crucial for assessing global chan...