Results 61 to 70 of about 6,506,964 (218)

Heavy subgraph pairs for traceability of block-chains

open access: yesDiscussiones Mathematicae Graph Theory, 2014
A graph is called traceable if it contains a Hamilton path, i.e., a path containing all its vertices. Let G be a graph on n vertices. We say that an induced subgraph of G is o−1-heavy if it contains two nonadjacent vertices which satisfy an Ore-type ...
Li Binlong   +2 more
doaj   +1 more source

Assessing the relation between protein phosphorylation, AlphaFold3 models, and conformational variability

open access: yesProtein Science, Volume 35, Issue 1, January 2026.
Abstract Proteins perform diverse functions critical to cellular processes. Transitions between functional states are often regulated by post‐translational modifications (PTMs) such as phosphorylation, which dynamically influence protein structure, function, folding, and interactions.
Pathmanaban Ramasamy   +3 more
wiley   +1 more source

Doubly Nonnegative and Semidefinite Relaxations for the Densest k-Subgraph Problem

open access: yesEntropy, 2019
The densest k-subgraph (DkS) maximization problem is to find a set of k vertices with maximum total weight of edges in the subgraph induced by this set. This problem is in general NP-hard. In this paper, two relaxation methods for solving the DkS problem
Chuan-Hao Guo, Yuan Guo, Bei-Bei Liu
doaj   +1 more source

Divisive Algorithm Based on Node Clustering Coefficient for Community Detection

open access: yesIEEE Access, 2020
This paper studies the relationship between the clustering coefficient of nodes and the community structure of the network. Communities in a network are regarded as node-induced subgraphs of the network in this study.
Qingbin Ji, Deyu Li, Zhen Jin
doaj   +1 more source

A Refined Graph Container Lemma and Applications to the Hard‐Core Model on Bipartite Expanders

open access: yesRandom Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT We establish a refined version of a graph container lemma due to Galvin and discuss several applications related to the hard‐core model on bipartite expander graphs. Given a graph G$$ G $$ and λ>0$$ \lambda >0 $$, the hard‐core model on G$$ G $$ at activity λ$$ \lambda $$ is the probability distribution μG,λ$$ {\mu}_{G,\lambda } $$ on ...
Matthew Jenssen   +2 more
wiley   +1 more source

A graph theoretical analysis of the number of edges in k-dense graphs

open access: yesElectronic Journal of Graph Theory and Applications, 2016
Due to the increasing discovery and implementation of networks within all disciplines of life, the study of subgraph connectivity has become increasingly important.
Linda Eroh   +4 more
doaj   +1 more source

Counting Independent Sets in Percolated Graphs via the Ising Model

open access: yesRandom Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT Given a graph G$$ G $$, we form a random subgraph Gp$$ {G}_p $$ by including each edge of G$$ G $$ independently with probability p$$ p $$. We provide an asymptotic expansion of the expected number of independent sets in random subgraphs of regular bipartite graphs satisfying certain vertex‐isoperimetric properties, extending the work of ...
Anna Geisler   +3 more
wiley   +1 more source

The Phylogeny Graphs of Doubly Partial Orders

open access: yesDiscussiones Mathematicae Graph Theory, 2013
The competition graph of a doubly partial order is known to be an interval graph. The CCE graph and the niche graph of a doubly partial order are also known to be interval graphs if the graphs do not contain a cycle of length four and three as an induced
Park Boram, Sano Yoshio
doaj   +1 more source

Counting Induced Subgraphs: An Algebraic Approach to #W[1]-Hardness [PDF]

open access: hybrid, 2021
Julian Dörfler   +3 more
openalex   +1 more source

Locally Markov Walks on Finite Graphs

open access: yesRandom Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT Locally Markov walks are natural generalizations of classical Markov chains, where instead of a particle moving independently of the past, it decides where to move next depending on the last action performed at the current location. We introduce the concept of locally Markov walks and we describe their stationary distribution and recurrent ...
Robin Kaiser   +2 more
wiley   +1 more source

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