Results 281 to 290 of about 27,298 (312)
Predicting protein-protein interaction sites based on dynamic perception mechanism within a hierarchical E(n)-equivariant graph. [PDF]
Brief BioinformLi X +7 more
europepmc +1 more source
HarveST uses a heterogeneous graph learning framework to reveal spatial transcriptomics patterns. [PDF]
Commun BiolFeng J, Yu T, Zhang Y.
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Coherent-resonant netting: disorder-enhanced selectivity from transient wave-like dynamics on biological connectomes. [PDF]
Front Comput NeurosciDolgikh O.
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Combinatorica, 1996
To each graph \(H\) on \(n\) vertices we may associate a 2-coloring of the edges of the complete graph \(K_n\) by taking the edges of \(H\) to be one color class and the edges of its complement \(\overline H\) to be the other. Given a coloring \(H\), we define \(c(G; H)\) to be the proportion of the copies of \(G\) in \(K_n\) which are monochromatic ...
Chris Jagger +2 more
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To each graph \(H\) on \(n\) vertices we may associate a 2-coloring of the edges of the complete graph \(K_n\) by taking the edges of \(H\) to be one color class and the edges of its complement \(\overline H\) to be the other. Given a coloring \(H\), we define \(c(G; H)\) to be the proportion of the copies of \(G\) in \(K_n\) which are monochromatic ...
Chris Jagger +2 more
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The Subgraph Similarity Problem [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2009 Similarity is a well known weakening of bisimilarity where one system is required to simulate the other and vice versa. It has been shown that the subgraph bisimilarity problem, a variation of the subgraph isomorphism problem where isomorphism is ...
Francesco Ranzato, Francesco Tapparo
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The Subgraph Bisimulation Problem
IEEE Transactions on Knowledge and Data Engineering, 2003 We study the complexity of the Subgraph Bisimulation Problem, which relates to Graph Bisimulation as Subgraph Isomorphism relates to Graph Isomorphism, and we prove its NP-Completeness.
Agostino Dovier, Carla Piazza
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Combinatorica, 1996
\(f(G)\) denotes the maximum number of edges in a bipartite subgraph of any simple graph \(G\); \(f(e)\) dentoes the minimum of \(f(G)\) as \(G\) ranges over all graphs \(G\) having \(e\) edges. Erdös has conjectured that \(\limsup_{e\to\infty} \Biggl(f(e)-{e\over 2}+{-1+\sqrt{8e+1}\over 8}\Biggr)=\infty\). Theorem 1.1. There exist a positive constant \
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\(f(G)\) denotes the maximum number of edges in a bipartite subgraph of any simple graph \(G\); \(f(e)\) dentoes the minimum of \(f(G)\) as \(G\) ranges over all graphs \(G\) having \(e\) edges. Erdös has conjectured that \(\limsup_{e\to\infty} \Biggl(f(e)-{e\over 2}+{-1+\sqrt{8e+1}\over 8}\Biggr)=\infty\). Theorem 1.1. There exist a positive constant \
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Journal of Graph Theory, 1983
AbstractDefine a geodesic subgraph of a graph to be a subgraph H with the property that any geodesic of two points of H is in H. The trivial geodesic subgraphs are the complete graphs Kn' n ≧ 0, and G itself. We characterize all (finite, simple, connected) graphs with only the trivial geodesic subgraphs, and give an algorithm for their construction. We
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AbstractDefine a geodesic subgraph of a graph to be a subgraph H with the property that any geodesic of two points of H is in H. The trivial geodesic subgraphs are the complete graphs Kn' n ≧ 0, and G itself. We characterize all (finite, simple, connected) graphs with only the trivial geodesic subgraphs, and give an algorithm for their construction. We
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Subgraph Transversal of Graphs
Graphs and Combinatorics, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Networks, 1995
AbstractAlthough the general problem of subgraph isomorphism is NP‐complete, polynomial‐time algorithms exist for recognizing any fixed subgraph. However, certain subgraphs appear easier to recognize than others. In this paper, we present general algorithms for fixed‐subgraph isomorphism which improve or unify previous results.
Gopalakrishnan Sundaram, Steven Skiena
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AbstractAlthough the general problem of subgraph isomorphism is NP‐complete, polynomial‐time algorithms exist for recognizing any fixed subgraph. However, certain subgraphs appear easier to recognize than others. In this paper, we present general algorithms for fixed‐subgraph isomorphism which improve or unify previous results.
Gopalakrishnan Sundaram, Steven Skiena
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