These works are based either on the assumption of an underlying, given static network (or two static, separate networks for interaction and imitation [18]) or a coevolution and rewiring starting from a fully developed network that already includes all the participating elements.
It enables biologists to manipulate public as well as private gene expression, macromolecular interaction and annotation data; interactively query gene expression datasets using a network of seed genes of interest; integrate data from multiple networks; query multiple networks for interactions of interest; as well as store and selectively share both the data and the Results of analysis.
It enables biologists to analyze public as well as private gene expression, macromolecular interaction and annotation data; interactively query gene expression datasets; integrate data from multiple networks; query multiple networks for interactions of interest; store and selectively share the data as well as results of analyses.
to manipulate public as well as private gene expression, macromolecular interaction and annotation data; interactively query gene expression datasets; integrate data from multiple networks; query multiple networks for interactions of interest; and store and selectively share the data as well as the results of analyses.
Sliwa, J. & Freiwald, W. A. A dedicated network for social interaction processing in the primate brain.
Sliwa, J. & Freiwald, W. A. A Network for Social interaction understanding in the primate brain.
In the Bayesian network for epistatic interaction detection, we use a Metropolis-Hastings method to build a Markov chain to get the posterior probability for each edge from the SNP nodes to the disease status node.
In the Bayesian network for epistatic interaction detection, we are only concerned with one target node, the disease status node, and we want to detect its parent SNP nodes.
However, this network for gene interactions within the hypothalamus was only hypothetical, so further experiments were designed to test their putative interactions.
To analyze these population-specific networks with respect to their topological and biological features, these networks were first compared with the HPRD network for their interactions, degree, diameter, and average path length.
