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Systematic topology analysis and generation using degree correlations
2006
Computer communication review
We hope that a systematic method to analyze and synthesize topologies offers a significant improvement to the set of tools available to network topology and protocol researchers. ...
We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. ...
Acknowledgements We would like to thank Walter Willinger and Lun Li for their HOT topology data; Bradley Huffaker, David Moore, Marina Fomenkov, and kc claffy for their contributions at different stages ...
doi:10.1145/1151659.1159930
fatcat:ald4cnmtdrbqpccifyzshzslei
Systematic topology analysis and generation using degree correlations
2006
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications - SIGCOMM '06
We hope that a systematic method to analyze and synthesize topologies offers a significant improvement to the set of tools available to network topology and protocol researchers. ...
We first introduce the dK-series of probability distributions specifying all degree correlations within d-sized subgraphs of a given graph G. ...
Acknowledgements We would like to thank Walter Willinger and Lun Li for their HOT topology data; Bradley Huffaker, David Moore, Marina Fomenkov, and kc claffy for their contributions at different stages ...
doi:10.1145/1159913.1159930
dblp:conf/sigcomm/MahadevanKFV06
fatcat:adtk2mux3rhjplafih3ogjpdoa
Transition to reconstructibility in weakly coupled networks
2017
PLoS ONE
We explicate how local common cause and relay structures, heterogeneous in-degrees and non-local structural properties of the network generally hinder reconstructibility. ...
Here we systematically study the problem of reconstructing direct physical interaction networks from thresholding correlations. ...
In particular, what do correlations generally tell us about direct physical interactions in network dynamical systems? ...
doi:10.1371/journal.pone.0186624
pmid:29053744
pmcid:PMC5650155
fatcat:hfwste54ajfvhktjbt344wb5dq
Hexagonal Patterning of the Insect Compound Eye: Facet Area Variation, Defects, and Disorder
2016
Biophysical Journal
This work develops formalisms of size-topology correlation that are very general and can be potentially applied to other cellular structures near the onset of disorder. ...
Without free parameters, the simulation predicts the size-topology correlation for both wild-type and mutant eyes. ...
ACKNOWLEDGMENTS We thank Salvatore Torquato and Duyu Chen for fruitful conversations and helpful suggestions on order parameter analysis. ...
doi:10.1016/j.bpj.2016.11.004
pmid:28002749
pmcid:PMC5194618
fatcat:xciy3tuuybc7tb2uuaqjgxziqu
Rates of evolution and homoplasy
1992
The Paleontological Society Special Publications
Homoplasy is present in virtually every known systematic analysis and exists at all levels of the Linnaean hierarchy. ...
In order to control for results that were unique to a given tree topology, the same data sets were generated onto two very different tree topologies (a extensively bifurcated tree and a Hennigian comb) ...
Homoplasy is present in virtually every known systematic analysis and exists at all levels of the Ilnnaean hierarchy. ...
doi:10.1017/s2475262200006845
fatcat:d3ar46cobrdqnddl4blatxkfom
Gene essentiality and the topology of protein interaction networks
2005
Proceedings of the Royal Society of London. Biological Sciences
Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology. ...
We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. ...
We would like to thank Jean-Louis Sikorav and Arach Goldar for critical comments on the manuscript, and Raphaël Guérois for the automatic retrieval of the numbers of SGD curated references. ...
doi:10.1098/rspb.2005.3128
pmid:16087428
pmcid:PMC1559853
fatcat:d4ofyzeijvcnjheda73pdp6wne
Effect of dataset selection on the topological interpretation of protein interaction networks
2005
BMC Genomics
When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. ...
Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. ...
Simon Lovell and for insights and discussions. LH is supported by a CASE Studentship from the Biotechnology & Biological Sciences Research Council (BBSRC) and AstraZeneca. ...
doi:10.1186/1471-2164-6-131
pmid:16174296
pmcid:PMC1249571
fatcat:mrde7vpnibhghixn47vb5lilma
Classification of Complex Networks Based on Topological Properties
2013
2013 International Conference on Cloud and Green Computing
However, each one of these studies generally focuses on a very small number of topological measures and networks. In this work, we aim at using a more systematic approach. ...
However, each one of these studies generally focuses on a very small number of topological measures and networks. In this work, we aim at using a more systematic approach. ...
The first contribution of our work was to tackle the problem of identifying discriminant topological measures by using a systematic approach, in terms of amount of data, topological measures and analysis ...
doi:10.1109/cgc.2013.54
dblp:conf/cgc/KantarciL13
fatcat:c5vx5fgw7fgcripvxmmabeigea
Resting-state fMRI Signals of Intelligent People Wander in a Larger Space: Supplementary Material
[article]
2019
bioRxiv
pre-print
In the general framework of topological data analysis, using a well-established non-linear dimensionality reduction method, we show that indeed resting-state fMRI signals of intelligent individuals occupy ...
This may be interpreted as the functional equivalence of one of the most celebrated structural correlates of intelligence, its positive association with the total brain volume. ...
topological data analysis. ...
doi:10.1101/529362
fatcat:jwbvwgxporadvns5oosbpjfvau
A comparative analysis of knowledge acquisition performance in complex networks
[article]
2020
arXiv
pre-print
While some studies have analyzed the performance of the knowledge acquisition process in particular network topologies, here we performed a systematic performance analysis in well-known dynamics and topologies ...
We also found ambiguities in the feature space describing the learning curves, meaning that the same knowledge acquisition curve can be generated in different combinations of network topology and dynamics ...
To our knowledge, no previous study focused on a systematic analysis among the dynamics, networks, and the sequences generated by them. ...
arXiv:2007.12028v1
fatcat:srejchpuvzbrvalslciljjlo5u
Spectral Graph Partitioning Analysis of In Vitro Synthesized RNA Structural Folding
[chapter]
2006
Lecture Notes in Computer Science
Our analysis shows that the majority of synthetic RNAs possess between two to six vertices and their second eigenvalues lie between one and two. ...
Our statistical analysis (at 95 percentile) also reveals three criteria important for designing novel functional RNAs. ...
Fig. 4 depicts how the non-topological properties of the primary sequence (i.e., L and G/C) and of the secondary structure (i.e., PB and MFE) are correlated with varying degrees to the topological measures ...
doi:10.1007/11818564_10
fatcat:676pjmxyvbgc3oasa5neqfpjuy
Addressing head motion dependencies for small-world topologies in functional connectomics
2013
Frontiers in Human Neuroscience
This study provides a comprehensive examination of motion correction strategies on the relationship between motion and commonly used topological parameters. ...
At the individual-level, we evaluated different models of head motion regression and scrubbing, as well as the potential benefits of using partial correlation (estimated via graphical lasso) instead of ...
Milham), Brain and Behavior Research Foundation (R. ...
doi:10.3389/fnhum.2013.00910
pmid:24421764
pmcid:PMC3872728
fatcat:dkx6rg4vufaovjzldzivbtj5xi
Regularizing capacity of metabolic networks
2007
Physical Review E
Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. ...
We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. ...
] with degree correlations of 0.05, 0, +0.3, and −0.3, respectively. ...
doi:10.1103/physreve.75.041917
pmid:17500931
fatcat:acew3cadsbafbhzc7y3l3765ii
Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study
2012
PLoS ONE
Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. ...
TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based ...
Yufeng Zang and Dr. Michael P. Milham for kindly providing the Datasets.
Author Contributions ...
doi:10.1371/journal.pone.0032766
pmid:22412922
pmcid:PMC3295769
fatcat:witoa4otcrewja6w6fxxavjl7q
Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods
2010
PLoS ONE
These measures are used to quantify topological network features via macroscopic statistical properties. ...
We present the results of a large-scale analysis of protein-protein interaction networks. Precise null models are used in our analyses, allowing for reliable interpretation of the results. ...
We find that degree-degree correlations provide important and consistent information on PPIN topologies, but it is crucial that they are normalised correctly and that one uses robust and systematic methods ...
doi:10.1371/journal.pone.0012083
pmid:20805870
pmcid:PMC2923596
fatcat:lhyz7riojfbqtetiwqlmg76kei
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