Correspondingly, if a R head-to-head and tail-to-tail mirror graphs sequence could be generated from original CR network graph, the multi-path routing problem could be simplified to a single path routing problem in the mirror graphs sequence.
Other examples include: DNA, RNA or protein sequences (linear graphs), sequence fragment overlap graphs (interval graphs) for shotgun sequence assembly, genetic maps and multiple sequence alignments (partial orders).
Following a so-called overall graph sequence by a scheduler, the collision-free trajectories of AGVs are determined by solving a collection of mixed integer linear programming problems sequentially.
Given significant substructure pairs, for an arbitrary compound-protein (graph-sequence) pair, we can compute a binary vector of 10,000 elements where if a significant substructure pair is included, the value of the corresponding element is 1; otherwise zero.
Currently many drug-target pairs are already known, by which we can take a data-driven approach to search substructure pairs significantly shared in the drug-target (graph-sequence) pairs.
The scalability of GRASP fingerprints on finding the most similar drug-target pair to an arbitrary given compound-protein (graph-sequence) pair was examined by generating 975,243,103 compound-protein pairs (which we call MASS) from 140,937 bioactive compounds and 6,919 druggable proteins (Methods section and Methods S1).
Our algorithm has two key features: 1) Listing up all frequent substructure pairs (Fig. 1b): This is a mathematical issue of enumerating all frequent pairs of subgraphs and subsequences which appeared in more than a pre-specified percentage (which is called support) in given graph-sequence pairs.
The internal schema of the BiologicalNetworks database is shown in Figure 2. Four orthogonal types of biological data--graphs, sequences, histograms, and tree structures--are integrated to enable multi-scale data analysis for the host-pathogen studies.
A network matching algorithm is proposed for matching the de Bruijn graph of contigs against reference genes, to derive 'gene paths' in the graph (sequences of contigs containing gene fragments) that have the highest similarities to known genes, allowing gene fragments contained in multiple contigs to be connected to form more complete (or intact) genes.
Velvet uses de-Bruijn graphs for sequence assembly and is specifically designed for short-read sequences.
The possible sequences of states that can take place in a network according to the logical functions and the chosen switching schemes can be represented in a state transition graph (also called graph of sequence of states; see [ 36]).
