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Graph annotations in modeling complex network topologies

Xenofontas Dimitropoulos, Dmitri Krioukov, Amin Vahdat, George Riley
2009 ACM Transactions on Modeling and Computer Simulation  
We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network.  ...  In this work, we abstract such additional information as network annotations.  ...  CONCLUSIONS In this work, we have focused on the problem of generating synthetic annotated graphs that model real complex net- works.  ... 
doi:10.1145/1596519.1596522 fatcat:bwatzldskzggjbkqbb73me7rie

GridG

Dong Lu, Peter A. Dinda
2003 Performance Evaluation Review  
We then describe the GridG process in two steps: topology generation and annotation. For topology generation, we have both a model and a mechanism.  ...  We leverage Tiers, an existing tool commonly used in the networking community, but we extend it to produce graphs that conform to recently discovered power laws of Internet topology.  ...  The graph is a thus a network topology that extends to the level of hosts. In addition, each node or edge is annotated with information relevant to its use as a part of a computational grid.  ... 
doi:10.1145/773056.773063 fatcat:r7sxoabkw5h4bbz3kw6kedbi34

Weaving Social Foundations Through Dance Pedagogy: A Pedagogy of Uncovering

Sherrie Barr, Doug Risner
2014 Journal of Dance Education  
The former approach enables quick and easy delineation of individual annotations and allows for complex topologies with multiple graph components.  ...  We also selected the Standards for Networking Ancient Prosopographies (SNAP) ontology for representation of the social network in the annotations, and the Open Annotation (OA) data model for serialization  ... 
doi:10.1080/15290824.2014.934985 fatcat:gzmgebsdovcpbenzxnl4xdoxtu

Predicting protein complex in protein interaction network - a supervised learning based method

Feng Yu, Zhi Yang, Nan Tang, Hong Lin, Jian Wang, Zhi Yang
2014 BMC Systems Biology  
The model utilizes additional "uncertainty" samples and, therefore, is more discriminative when used in the complex detection algorithm.  ...  Methods: We present a supervised learning-based method for predicting protein complexes in protein -protein interaction networks.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.1186/1752-0509-8-s3-s4 pmid:25349902 pmcid:PMC4243764 fatcat:okl7vo7pbbgj5cra64nrmrf2ey

Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins

William P Kelly, Michael PH Stumpf
2010 BMC Bioinformatics  
In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.  ...  We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.  ...  , and molecular function [function]; and multi-protein complex annotations [complex] found in [38] .  ... 
doi:10.1186/1471-2105-11-470 pmid:20854660 pmcid:PMC2955699 fatcat:xgtq7movhrdpdpqgxpoeojfgx4

Graph analysis and clustering of proteins linked with COVID-19

J. Susymary, P. Deepalakshmi
2022 International Journal of Intelligent Decision Technologies  
Topological means of graph analysis and graph clustering have been employed to group proteins that possess the same biological functions.  ...  The detection of COVID-19 protein complexes, a group of proteins that possess the same biological functions, helps in better understanding of the biological processes in our body.  ...  Topological means of PPI network analysis provide a platform for exploring complex diseases [13] [14] [15] .  ... 
doi:10.3233/idt-200185 fatcat:oklmlxabkrauxo7wmyugbbrzga

Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks

Ignat Drozdov, Christos A Ouzounis, Ajay M Shah, Sophia Tsoka
2011 BMC Research Notes  
Findings: We present Functional Genomics Assistant (FUGA) -an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network  ...  Conclusion: FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at  ...  Early stages of this work have been supported in part by the Network of Excellence ENFIN (contract number LSHG-CT-2005-518254) funded by the European Commission.  ... 
doi:10.1186/1756-0500-4-462 pmid:22035155 pmcid:PMC3214203 fatcat:jnwf4zc6urbppaizrt262qgi2e

The workshop on internet topology (wit) report

Dmitri Krioukov, kc claffy, Marina Fomenkov, Fan Chung, Alessandro Vespignani, Walter Willinger
2007 Computer communication review  
As a result, the field of Internet topology analysis and modeling must untangle sets of inconsistent findings, conflicting claims, and contradicting statements.  ...  Internet topology analysis has recently experienced a surge of interest in computer science, physics, and the mathematical sciences.  ...  i) annotated models of an ISP's router-level topology, where nodes are labeled with router capacity, type, or role, and link labels describe delay, distance, or bandwidth; (ii) annotated models of the  ... 
doi:10.1145/1198255.1198267 fatcat:btx5t32hirad5cdjhdseih7qpu

Higher-order molecular organization as a source of biological function

Thomas Gaudelet, Noël Malod-Dognin, Nataša Pržulj
2018 Bioinformatics  
Molecular interactions have widely been modelled as networks. The local wiring patterns around molecules in molecular networks are linked with their biological functions.  ...  hidden in the wiring patterns of molecular systems modelled as hypernetworks.  ...  Simple graphs (also called networks) have been widely used to model the interactions between pairs of molecules.  ... 
doi:10.1093/bioinformatics/bty570 pmid:30423061 pmcid:PMC6129285 fatcat:m54gy3k7zjaavbijmcpnv3zcpq

Bridging topological and functional information in protein interaction networks by short loops profiling

Sun Sook Chung, Alessandro Pandini, Alessia Annibale, Anthony C. C. Coolen, N. Shaun B. Thomas, Franca Fraternali
2015 Scientific Reports  
In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins.  ...  protein complexes.  ...  Thirdly, we estimated the statistical significance of motifs by comparison with tailored random graph ensembles 21 with comparable topological constraints, instead of using a general random model.  ... 
doi:10.1038/srep08540 pmid:25703051 pmcid:PMC5224520 fatcat:iclr7khplfd4zhyqlgghsjqnqq

A Behavioral Approach to Visual Navigation with Graph Localization Networks [article]

Kevin Chen, Juan Pablo de Vicente, Gabriel Sepulveda, Fei Xia, Alvaro Soto, Marynel Vazquez, Silvio Savarese
2019 arXiv   pre-print
We propose using graph neural networks for localizing the agent in the map, and decompose the action space into primitive behaviors implemented as convolutional or recurrent neural networks.  ...  Inspired by research in psychology, we introduce a behavioral approach for visual navigation using topological maps.  ...  These node and edge annotations were used for training the graph localization network, for running the GTL model, and for comparing our model with the baselines.  ... 
arXiv:1903.00445v1 fatcat:mbktv36zvrevzklj2qw3rposfe

Biological context networks: a mosaic view of the interactome

John Rachlin, Dikla Dotan Cohen, Charles Cantor, Simon Kasif
2006 Molecular Systems Biology  
Network models are a fundamental tool for the visualization and analysis of molecular interactions occurring in biological systems.  ...  In this paper, we introduce a novel graph construct called a biological context network that explicitly captures these changing patterns of interaction from one biological context to another.  ...  This work was supported in part by NSF grants DBI-0239435 and ITR-048715, NHGRI grant #1R33HG002850-01A1, and NIH grant U54 LM008748.  ... 
doi:10.1038/msb4100103 pmid:17130868 pmcid:PMC1693461 fatcat:sds2jfm45fbyjaoq26r4pfbewa

Orbis

Priya Mahadevan, Calvin Hubble, Dmitri Krioukov, Bradley Huffaker, Amin Vahdat
2007 Computer communication review  
must closely match real network characteristics, not just in terms of graph structure (node interconnectivity) but also with respect to various node and link annotations.  ...  In this paper, we propose techniques to generate annotated, Internet router graphs of different sizes based on existing observations of Internet characteristics.  ...  This research was supported in part by a National Science Foundation Grant (CNS-0627145) and UCSD's Center for Networked Systems.  ... 
doi:10.1145/1282427.1282417 fatcat:igmzve2zfzhp7jenbywavy5lky

graphite - a Bioconductor package to convert pathway topology to gene network

Gabriele Sales, Enrica Calura, Duccio Cavalieri, Chiara Romualdi
2012 BMC Bioinformatics  
In the field of topological analysis graphite acts as a provider of biological information by reducing the pathway complexity considering the biological meaning of the pathway elements.  ...  gene families and sensibly removing chemical compounds from the final graphs.  ...  In the graphite network the nodes are annotated using the XRefs informations while edges preserve the type of the reaction annotated the OWL model.  ... 
doi:10.1186/1471-2105-13-20 pmid:22292714 pmcid:PMC3296647 fatcat:hkbk3e5rgze5vmmwj7b52n5zbu

Network-based prediction of protein function

Roded Sharan, Igor Ulitsky, Ron Shamir
2007 Molecular Systems Biology  
functional modules within the network and use those for the annotation task.  ...  The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function.  ...  Figure 1 1 Extent of annotation of proteins in model species.  ... 
doi:10.1038/msb4100129 pmid:17353930 pmcid:PMC1847944 fatcat:c7m7kdztsfd43e2sfsfnow2j2m
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