Results 31 to 40 of about 32,903 (262)

On α-adjacency energy of graphs and Zagreb index

open access: yesAKCE International Journal of Graphs and Combinatorics, 2021
Let A(G) be the adjacency matrix and D(G) be the diagonal matrix of the vertex degrees of a simple connected graph G. Nikiforov defined the matrix of the convex combinations of D(G) and A(G) as for If are the eigenvalues of (which we call α-adjacency ...
S. Pirzada   +3 more
doaj   +1 more source

On the Adjacency, Laplacian, and Signless Laplacian Spectrum of Coalescence of Complete Graphs

open access: yesJournal of Mathematics, 2016
Coalescence as one of the operations on a pair of graphs is significant due to its simple form of chromatic polynomial. The adjacency matrix, Laplacian matrix, and signless Laplacian matrix are common matrices usually considered for discussion under ...
S. R. Jog, Raju Kotambari
doaj   +1 more source

KAMG: A Tool for Converting Blood Ties and Affinity Ties into Adjacency Matrices

open access: yesJournal of Open Research Software, 2016
Kinship Adjacency Matrix Generator (KAMG) is a browser-based software for creating adjacency matrices using the information of kinship ties. Specifically, it is capable of converting the family trees in the format of GEDCOM files into adjacency matrices ...
Hang Xiong, Pin Xiong, Hui Xiong
doaj   +1 more source

From mice to humans—divergent strategies for intestinal homeostasis and regeneration

open access: yesFEBS Letters, EarlyView.
Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa   +2 more
wiley   +1 more source

Multivariate Fence: Using Parallel Coordinates to Locate and Compare Attributes of Adjacency Matrix Nodes in Immersive Environment

open access: yesApplied Sciences, 2022
Adjacency matrix visualization is a common method for presenting graph data, and the Focus+Context technique can be used to explore the details of the ROI (region of interest).
Tiemeng Li   +3 more
doaj   +1 more source

Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation

open access: yesFEBS Letters, EarlyView.
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang   +2 more
wiley   +1 more source

On the adjacency matrix of a block graph [PDF]

open access: yesLinear and Multilinear Algebra, 2013
A block graph is a graph in which every block is a complete graph. Let be a block graph and let be the adjacency matrix of . We first obtain a formula for the determinant of over reals. It is shown that is nonsingular over if and only if the removal of any vertex from produces a graph with exactly one odd component. A formula for the inverse of over is
R.B. Bapat, Souvik Roy
openaire   +1 more source

Metastatic niche shaped by host factors influences disseminated cancer cell fate

open access: yesFEBS Letters, EarlyView.
Metastasis is shaped not only by cancer cells but also by the environments they encounter. This review explores how factors such as aging, diet, the microbiome, lifestyle, and environmental exposures remodel organ‐specific niches in the lung, liver, bone, and brain, influencing where metastatic cells survive, remain dormant, or grow, and ultimately ...
Gwennan Delyth Ward   +2 more
wiley   +1 more source

Deep Learning Techniques for Community Detection in Social Networks

open access: yesIEEE Access, 2020
Graph embedding is an effective yet efficient way to convert graph data into a low dimensional space. In recent years, deep learning has applied on graph embedding and shown outstanding performance.
Ling Wu   +4 more
doaj   +1 more source

Spatial‐temporal slowfast graph convolutional network for skeleton‐based action recognition

open access: yesIET Computer Vision, 2022
In skeleton‐based action recognition, the graph convolutional network (GCN) has achieved great success. Modelling skeleton data in a suitable spatial‐temporal way and designing the adjacency matrix are crucial aspects for GCN‐based methods to capture ...
Zheng Fang   +4 more
doaj   +1 more source

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