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  1. 1181
    “…Mapping network nodes and edges to communities and network functions is crucial to gaining a higher level of understanding of the network structure and functions. …”
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    Network Analytics Enabled by Generating a Pool of Network Variants from Noisy Data
  2. 1182
    “…Our solution is a heterogeneous wireless network fault diagnosis algorithm based on Graph Convolutional Neural Network (GCN). …”
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    Cellular Network Fault Diagnosis Method Based on a Graph Convolutional Neural Network
  3. 1183
    “…We measure key network themes of connectivity, health and results, and impact and return on investment associated with health research networks. …”
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    Describing the state of a research network: A mixed methods approach to network evaluation
  4. 1184
    “…This paper presents path loss prediction models based on machine learning algorithms, namely artificial neural network (ANN), artificial recurrent neural network (RNN) based on long short-term memory (LSTM), shortly known as RNN-LSTM, and convolutional neural network (CNN). …”
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    Path loss modeling based on neural networks and ensemble method for future wireless networks
  5. 1185
    por Deng, Lei, Ren, Shengli, Zhang, Jingpu
    Publicado 2023
    “…RESULTS: In this paper, we propose a new computational method based on global heterogeneous networks to predict the functions of lncRNAs, called DNGRGO. …”
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    Prediction of lncRNA functions using deep neural networks based on multiple networks
  6. 1186
    “…We assessed functional connectivity (FC) between regions of interest (ROIs) in the fronto-parietal control network (PFCN) and sensorimotor network (SMN). We also examined the relationship between altered FC and behavioral data. …”
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    Functional connectivity alterations in the frontoparietal network and sensorimotor network are associated with behavioral heterogeneity in blepharospasm
  7. 1187
    “…OBJECTIVE: Investigate the brain functional networks associated with motor impairment in people with Parkinson’s disease (PD). …”
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    Motor networks, but also non-motor networks predict motor signs in Parkinson’s disease
  8. 1188
    “…INTRODUCTION: State tobacco control programs are implemented by networks of public and private agencies with a common goal to reduce tobacco use. …”
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    Interorganizational Relationships Within State Tobacco Control Networks: A Social Network Analysis
  9. 1189
    por Meshi, Ofer, Shlomi, Tomer, Ruppin, Eytan
    Publicado 2007
    “…BACKGROUND: Localized network patterns are assumed to represent an optimal design principle in different biological networks. …”
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    Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network
  10. 1190
    “…BACKGROUND: It has been recognized that modular organization pervades biological complexity. Based on network analysis, ‘party hubs’ and ‘date hubs’ were proposed to understand the basic principle of module organization of biomolecular networks. …”
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    Hubs with Network Motifs Organize Modularity Dynamically in the Protein-Protein Interaction Network of Yeast
  11. 1191
    por Humphries, Mark D., Gurney, Kevin
    Publicado 2008
    “…BACKGROUND: Many technological, biological, social, and information networks fall into the broad class of ‘small-world’ networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). …”
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    Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence
  12. 1192
    “…BACKGROUND: Protein-protein interaction networks are commonly sampled using yeast two hybrid approaches. …”
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    Deducing topology of protein-protein interaction networks from experimentally measured sub-networks
  13. 1193
    “…We devise a method that extends Network Component Analysis (NCA) to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs) perturb these two properties. …”
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    Using Network Component Analysis to Dissect Regulatory Networks Mediated by Transcription Factors in Yeast
  14. 1194
    “…RESULTS: In this paper, we propose Deterministic Effects Propagation Networks (DEPNs) as a special Bayesian Network approach to reverse engineer signaling networks from a combination of protein expression and perturbation data. …”
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    Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventions
  15. 1195
    “…BACKGROUND: Network Component Analysis (NCA) is a network structure-driven framework for deducing regulatory signal dynamics. …”
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    Inferring a transcriptional regulatory network of the cytokinesis-related genes by network component analysis
  16. 1196
    por Alvarez, Angel, Woolf, Peter J
    Publicado 2011
    “…The Partially Observed Bipartite Network (POBN) approach developed here is tested using E. coli expression data and a transcriptional regulatory network derived from RegulonDB. …”
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    Partially observed bipartite network analysis to identify predictive connections in transcriptional regulatory networks
  17. 1197
    por Chadick, James Z., Gazzaley, Adam
    Publicado 2011
    “…The relationship between top-down enhancement and suppression of sensory cortical activity and large-scale, neural-networks remains unclear. Functional connectivity analysis of human fMRI data revealed visual cortical areas that selectively process relevant information are functionally connected with the frontal-parietal network, while those processing irrelevant information are simultaneously coupled with the default-network. …”
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    Differential coupling of visual cortex with default network or frontal-parietal network based on goals
  18. 1198
    “…In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. …”
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    On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks
  19. 1199
    “…Network motifs, overrepresented small local connection patterns, are assumed to act as functional meaningful building blocks of a network and, therefore, received considerable attention for being useful for understanding design principles and functioning of networks. …”
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    An Analytical Approach to Network Motif Detection in Samples of Networks with Pairwise Different Vertex Labels
  20. 1200
    “…Network motifs are small connected sub-graphs that have recently gathered much attention to discover structural behaviors of large and complex networks. …”
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    Online Artículo Texto
    CytoKavosh: A Cytoscape Plug-In for Finding Network Motifs in Large Biological Networks
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