Contributors: Electrical and Computer Engineering
Subject Terms: Power system, Koopman modes analysis, Controlled islanding, Coherency, Subgraph
File Description: application/pdf
Relation: http://hdl.handle.net/10919/98249; 16
Availability: http://hdl.handle.net/10919/98249
Subject Terms:
Microbiology, Cell Biology, Genetics, Molecular Biology, Evolutionary Biology, Cancer, Infectious Diseases, Plant Biology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, play central roles, induced subgraph ), cancer mechanisms described, given graphlet adjacency, pathways p, graphlet adjacencies captured, cancer mechanisms, graphlet adjacency, graphlet adjacencies, given graphlet, pathways described, new graphlet,
Availability: https://doi.org/10.1371/journal.pone.0261676.g002
Subject Terms:
Microbiology, Cell Biology, Genetics, Molecular Biology, Evolutionary Biology, Cancer, Infectious Diseases, Plant Biology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, play central roles, induced subgraph ), cancer mechanisms described, given graphlet adjacency, pathways p, graphlet adjacencies captured, cancer mechanisms, graphlet adjacency, graphlet adjacencies, given graphlet, pathways described, new graphlet,
Availability: https://doi.org/10.1371/journal.pone.0261676.g005
Subject Terms:
Microbiology, Cell Biology, Genetics, Molecular Biology, Evolutionary Biology, Cancer, Infectious Diseases, Plant Biology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, play central roles, induced subgraph ), cancer mechanisms described, given graphlet adjacency, pathways p, graphlet adjacencies captured, cancer mechanisms, graphlet adjacency, graphlet adjacencies, given graphlet, pathways described, new graphlet,
Relation: https://figshare.com/articles/figure/An_illustration_of_graphlets_and_graphlet_adjacencies_/19065507
Availability: https://doi.org/10.1371/journal.pone.0261676.g001
Subject Terms:
Microbiology, Cell Biology, Genetics, Molecular Biology, Evolutionary Biology, Cancer, Infectious Diseases, Plant Biology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, play central roles, induced subgraph ), cancer mechanisms described, given graphlet adjacency, pathways p, graphlet adjacencies captured, cancer mechanisms, graphlet adjacency, graphlet adjacencies, given graphlet, pathways described, new graphlet,
Availability: https://doi.org/10.1371/journal.pone.0261676.g003
Subject Terms:
Microbiology, Cell Biology, Genetics, Molecular Biology, Evolutionary Biology, Cancer, Infectious Diseases, Plant Biology, Environmental Sciences not elsewhere classified, Biological Sciences not elsewhere classified, Mathematical Sciences not elsewhere classified, play central roles, induced subgraph ), cancer mechanisms described, given graphlet adjacency, pathways p, graphlet adjacencies captured, cancer mechanisms, graphlet adjacency, graphlet adjacencies, given graphlet, pathways described, new graphlet,
Availability: https://doi.org/10.1371/journal.pone.0261676.g004
Authors: Yao Li, Zihao Zhou, Qifan Li, Tao Li, Ibegbu Nnamdi Julian, Hao Guo, Junjie Chen
Subject Terms: Neuroscience, Biological Engineering, Developmental Biology, Stem Cells, Artificial Intelligence and Image Processing, Endocrinology, Radiology and Organ Imaging, Autonomic Nervous System, Cellular Nervous System, Central Nervous System, Sensory Systems, Clinical Nursing: Tertiary (Rehabilitative), Decision Making, Rehabilitation Engineering, Biomedical Engineering not elsewhere classified, Signal Processing, Neurogenetics, Image Processing, frequent subgraph mining, discriminative feature selection, machine learning, classification, fMRI, depression, uncertain brain network
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.s002
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g001
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g002
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g003
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g004
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g005
Authors: Meghana Venkata Palukuri, Edward M. Marcotte
Subject Terms: Biochemistry, Cancer, Biological Sciences not elsewhere classified, Information Systems not elsewhere classified, overlapping community detection, community detection methods, 234 complexes linked, dense network subgraphs, learned community characteristics, molecular complex detection, complex outperforms 6, 103 learned complexes, known communities satisfactorily, div >< p, community fitness function, 4 unsupervised methods, potential protein complexes, 028 protein complexes, known communities using, detect new communities, known communities, fitness function, protein complexes, detect communities, using better, interaction network, complex learns, yeast protein, protein interactions, human protein
Availability: https://doi.org/10.1371/journal.pone.0262056.g003