Results 81 to 90 of about 146,643 (141)

An Effective Graph Clustering Method to Identify Cancer Driver Modules. [PDF]

Front Bioeng Biotechnol, 2020
Zhang W, Zeng Y, Wang L, Liu Y, Cheng YN.   +4 more
europepmc   +1 more source

Subphenotyping sepsis based on organ interaction trajectory using a deep temporal graph clustering model: a retrospective cohort study. [PDF]

EClinicalMedicine
Feng X, Sun L, Zhu J, Yao X, Zhang Z, Pan Q, Fang L, Ning G.   +7 more
europepmc   +1 more source

Differentiable graph clustering with structural grouping for single-cell RNA-seq data. [PDF]

Bioinformatics
Yan X, Du S, Zou Q, Tian Z.
europepmc   +1 more source

m2ST: dual multi-scale graph clustering for spatially resolved transcriptomics. [PDF]

Bioinformatics
Zhang W, Zhang Z, Yang H, Zhang T, Jiang S, Qiao N, Deng Z, Pan X, Shen HB, Yu DJ, Wang S.   +10 more
europepmc   +1 more source

The Utility of Graph Clustering of 5S Ribosomal DNA Homoeologs in Plant Allopolyploids, Homoploid Hybrids, and Cryptic Introgressants. [PDF]

Front Plant Sci, 2020
Garcia S, Wendel JF, Borowska-Zuchowska N, Aïnouche M, Kuderova A, Kovarik A.   +5 more
europepmc   +1 more source

Two antagonistic objectives for one multi-scale graph clustering framework. [PDF]

Sci Rep
Gaume B, Achitouv I, Chavalarias D.
europepmc   +1 more source

Triangulating Clustered Graphs

, 2002
A clustered graph C=(G,T) consists of an undirected graph G and a rooted tree T in which the leaves of T correspond to the vertices of G=(V,E) . Each vertex mu in T corresponds to a subset of the vertices of the graph called ''cluster''. C -planarity is a natural extension of graph planarity for clustered graphs.
Jünger, Michael, Leipert, Sebastian, Percan, Merijam   +2 more
openaire   +1 more source

Robust self supervised symmetric nonnegative matrix factorization to the graph clustering. [PDF]

Sci Rep
Ru Y, Gruninger M, Dou Y.
europepmc   +1 more source

An edge server placement based on graph clustering in mobile edge computing. [PDF]

Sci Rep
Zhang S, Yu J, Hu M.
europepmc   +1 more source

The influence maximization algorithm for integrating attribute graph clustering and heterogeneous graph transformer. [PDF]

Heliyon
Zhang W, Liu Z.
europepmc   +1 more source