Results 61 to 70 of about 38,730 (201)

Detection of Network Motif Based on a Novel Graph Canonization Algorithm from Transcriptional Regulation Networks

open access: yesMolecules, 2017
Network motifs are patterns of complex networks occurring significantly more frequently than those in random networks. They have been considered as fundamental building blocks of complex networks.
Jialu Hu, Xuequn Shang
doaj   +1 more source

Self-Dual and LCD Codes from Kneser Graphs K(n, 2) and Generalized Quadrangles

open access: yesMathematics
In this paper, we study self-dual and LCD codes constructed from Kneser graphs K(n, 2) and collinearity graphs of generalized quadrangles using the so-called pure and bordered construction. We determine conditions under which these codes are self-dual or
Dean Crnković, Ana Grbac
doaj   +1 more source

Some New Cyclotomic Strongly Regular Graphs [PDF]

open access: yesJournal of Algebraic Combinatorics, 1995
Given a field \(F\) and a subset \(D\) of \(F^*\) such that \(D= -D\), one can define a graph \(\Gamma\) with vertex set \(F\) by letting \(x\sim y\) whenever \(y- x\in D\). Several authors have studied the problem of finding sets \(D\) such that the graph \(\Gamma\) is strongly regular and many examples are known.
openaire   +2 more sources

Identifying Codes in Vertex-Transitive Graphs and Strongly Regular Graphs [PDF]

open access: diamond, 2015
Sylvain Gravier   +4 more
openalex   +1 more source

q-analogs of strongly regular graphs

open access: yesLinear Algebra and its Applications
We introduce the notion of q-analogs of strongly regular graphs and give several examples of such structures. We prove a necessary condition on the parameters, show the connection to designs over finite fields, and present a classification.
Michael Braun   +4 more
openaire   +3 more sources

Strongly Regular Fusions of Tensor Products of Strongly Regular Graphs

open access: yesRocky Mountain Journal of Mathematics, 1994
Let \(G\) and \(H\) be strongly regular graphs with (0, 1)-adjacency matrices \(A_ 0= I\), \(A_ 1\), \(A_ 2= J-I- A_ 1\) and \(B_ 0= I\), \(B_ 1,\) \(B_ 2= J- I- B_ 1\) respectively. The tensor product \(G\otimes H\) is defined to be the nine class association scheme with adjacency matrices \(A_ i\otimes B_ j\). By combining (fusing) some of these nine
openaire   +2 more sources

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