Results 91 to 100 of about 946,691 (269)

GlycoChat Uncovers Glycan–Lectin Circuits in the Tumor Microenvironment of Pancreatic Cancer

open access: yesAdvanced Science, EarlyView.
Aberrant glycosylation drives cancer progression, yet its role in the tumor microenvironment remains unclear. We developed GlycoChat to map glycan–lectin circuits at single‐cell resolution. We discovered that cancer cells induce immunosuppressive macrophage differentiation and impair phagocytosis through interactions with CLEC10A and SIGLEC3 ...
Dinh Xuan Tuan Anh   +8 more
wiley   +1 more source

On rank-width of even-hole-free graphs [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science, 2017
We present a class of (diamond, even hole)-free graphs with no clique cutset that has unbounded rank-width. In general, even-hole-free graphs have unbounded rank-width, because chordal graphs are even-hole-free. A.A. da Silva, A. Silva and C.
Isolde Adler   +5 more
doaj   +1 more source

3-Colourability of Dually Chordal Graphs in Linear Time [PDF]

open access: yes, 2012
A graph G is dually chordal if there is a spanning tree T of G such that any maximal clique of G induces a subtree in T. This paper investigates the Colourability problem on dually chordal graphs.
Leitert, Arne
core  

Chordal multipartite graphs and chordal colorings

open access: yesDiscrete Mathematics, 2007
A graph is defined to be chordal colorable if it admits a proper vertex-coloring such that each minimal separator induces a subgraph in which two vertices are adjacent if and only if they are differently colored. All chordal graphs and all chordal bipartite graphs are chordal colorable. All chordal colorable graphs are weakly chordal.
openaire   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

open access: yesAdvanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu   +6 more
wiley   +1 more source

Distance Approximating Trees for Chordal and Dually Chordal Graphs [PDF]

open access: yesJournal of Algorithms, 1999
Summary: We show that, for each chordal graph \(G\), there is a tree \(T\) such that \(T\) is a spanning tree of the square \(G^2\) of \(G\) and, for every two vertices, the distance between them in \(T\) is not larger than the distance in \(G\) plus 2.
Brandstädt, Andreas   +2 more
openaire   +2 more sources

m1A‐Dependent TRMT6/61A‐ARG2 Axis Drives Protumorigenic Senescence by Remodeling the Tumor Microenvironment

open access: yesAdvanced Science, EarlyView.
Uncovering a new layer of translational control, this study reveals how TRMT6/TRMT61A‐mediated tRNA‐m1A methylation drives pro‐tumorigenic senescence in colorectal cancer. By selectively enhancing ARG2 translation, this epitranscriptomic axis triggers an NF‐κB‐dependent SASP.
Tuoyang Li   +17 more
wiley   +1 more source

End Simplicial Vertices in Path Graphs

open access: yesDiscussiones Mathematicae Graph Theory, 2016
A graph is a path graph if there is a tree, called UV -model, whose vertices are the maximal cliques of the graph and for each vertex x of the graph the set of maximal cliques that contains it induces a path in the tree.
Gutierrez Marisa, Tondato Silvia B.
doaj   +1 more source

Dualizing chordal graphs

open access: yesDiscrete Mathematics, 2003
This paper studies dual-chordal graphs, that is, graphs that are dual to chordal graphs with regard to cycle/cutset duality. A characteristic of such graphs is that every cutset with at least four edges is accompanied by a certain kind of edge, a ``cut-chord.'' One result allows us to recognize dual-chordal graphs by simply looking at cubic graphs.
openaire   +1 more source

Generating Weakly Chordal Graphs from Arbitrary Graphs

open access: yes, 2022
We propose a scheme for generating a weakly chordal graph from a randomly generated input graph, G = (V, E). We reduce G to a chordal graph H by adding fill-edges, using the minimum vertex degree heuristic. Since H is necessarily a weakly chordal graph, we use an algorithm for deleting edges from a weakly chordal graph that preserves the weak ...
Khanduja, Sudiksha   +3 more
openaire   +2 more sources

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