In this study, we utilized the Klein-Ravi algorithm to generate a node-weighted Steiner tree subnetwork.
In Run(2), the enhancement generates a node of B z on its tailward side, and we found x/d∼−4.8 at Ω i t=8.4.
Just as for Run(2), the local B z enhancement also generates a node on its tailward side in Run(3).
Therefore, the enhancement quickly generates a node by the relaxation process, and the developing B z attains a greater value than that of Run(0) at Ω i t=8.4 and Ω i t=15.2.
Given an RNA secondary structure, each loop, base-pair, and interval of unpaired bases generates a node in the tree representation of the structure.
If a node detects a configurable number of anomalies in this time, it generates a node-level alarm in the system by sending a message through the VCC channel.
In a duplication process, a randomly selected node is duplicated to generate a new node having the same links as the original node, followed by a divergence process in which some links are eliminated.
Many of them are based on gene duplication and divergence, in which a randomly selected node is duplicated to generate a new node having the same links as the original node, and some links are added or eliminated in a divergence process [ 19- 23].
(1) A node is randomly selected (A) and is duplicated to generate a new node (A'), having the same interacting pattern as node A. (2) Each of the links to node A' is removed with a probability α (completely asymmetric divergence [44]).
If a low-degree node A is duplicated to generate a new node A', the value of ν in a network increases, because a degree of a node (C) connected to a low-degree node increases.
Node A is duplicated to generate a new node (A') with a probability (1 + σk)/1,000 (when 1 + σk >0), where k is the degree of node A, and σ is a parameter determining the duplicability of a node for each species.
