scholarly journals Trusted Interaction Patterns in Large-scale Enterprise Service Networks

2010 ◽  
Author(s):  
Florian Skopik ◽  
Daniel Schall ◽  
Schahram Dustdar
Keyword(s):  
Large Scale ◽  
Interaction Patterns ◽  
Service Networks

scholarly journals Erythrocytes 3D genome organization in vertebrates

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anastasia Ryzhkova ◽  
Alena Taskina ◽  
Anna Khabarova ◽  
Veniamin Fishman ◽  
Nariman Battulin
Keyword(s):  
Blood Cells ◽  
Genome Organization ◽  
Large Scale ◽  
Chromatin Condensation ◽  
Erythroid Differentiation ◽  
Interaction Patterns ◽  
3D Interaction ◽  
Interphase Chromosome ◽  
3D Genome ◽  
Contact Maps

AbstractGeneration of mature red blood cells, consisting mainly of hemoglobin, is a remarkable example of coordinated action of various signaling networks. Chromatin condensation is an essential step for terminal erythroid differentiation and subsequent nuclear expulsion in mammals. Here, we profiled 3D genome organization in the blood cells from ten species belonging to different vertebrate classes. Our analysis of contact maps revealed a striking absence of such 3D interaction patterns as loops or TADs in blood cells of all analyzed representatives. We also detect large-scale chromatin rearrangements in blood cells from mammals, birds, reptiles and amphibians: their contact maps display strong second diagonal pattern, representing an increased frequency of long-range contacts, unrelated to TADs or compartments. This pattern is completely atypical for interphase chromosome structure. We confirm that these principles of genome organization are conservative in vertebrate erythroid cells.

scholarly journals Automated monitoring of behavior reveals bursty interaction patterns and rapid spreading dynamics in honeybee social networks

2018 ◽  
Vol 115 (7) ◽  
pp. 1433-1438 ◽  
Author(s):  
Tim Gernat ◽  
Vikyath D. Rao ◽  
Martin Middendorf ◽  
Harry Dankowicz ◽  
Nigel Goldenfeld ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Interactions ◽  
Communication Networks ◽  
Disease Transmission ◽  
Large Scale ◽  
Reference Network ◽  
Interaction Patterns ◽  
Human Communication ◽  
Automated Monitoring ◽  
Phone Calls

Social networks mediate the spread of information and disease. The dynamics of spreading depends, among other factors, on the distribution of times between successive contacts in the network. Heavy-tailed (bursty) time distributions are characteristic of human communication networks, including face-to-face contacts and electronic communication via mobile phone calls, email, and internet communities. Burstiness has been cited as a possible cause for slow spreading in these networks relative to a randomized reference network. However, it is not known whether burstiness is an epiphenomenon of human-specific patterns of communication. Moreover, theory predicts that fast, bursty communication networks should also exist. Here, we present a high-throughput technology for automated monitoring of social interactions of individual honeybees and the analysis of a rich and detailed dataset consisting of more than 1.2 million interactions in five honeybee colonies. We find that bees, like humans, also interact in bursts but that spreading is significantly faster than in a randomized reference network and remains so even after an experimental demographic perturbation. Thus, while burstiness may be an intrinsic property of social interactions, it does not always inhibit spreading in real-world communication networks. We anticipate that these results will inform future models of large-scale social organization and information and disease transmission, and may impact health management of threatened honeybee populations.

Finding susceptible and protective interaction patterns in large-scale genetic association study

2017 ◽  
Vol 11 (3) ◽  
pp. 541-554 ◽  
Author(s):  
Yuan Li ◽  
Yuhai Zhao ◽  
Guoren Wang ◽  
Xiaofeng Zhu ◽  
Xiang Zhang ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Association ◽  
Genetic Association Study ◽  
Large Scale ◽  
Interaction Patterns

scholarly journals Chromosome-wise Protein Interaction Patterns and Their Impact on Functional Implications of Large-Scale Genomic Aberrations

Cell Systems ◽  
2017 ◽  
Vol 4 (3) ◽  
pp. 357-364.e3 ◽  
Author(s):  
Isa Kristina Kirk ◽  
Nils Weinhold ◽  
Kirstine Belling ◽  
Niels Erik Skakkebæk ◽  
Thomas Skøt Jensen ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Interaction Patterns ◽  
Functional Implications ◽  
Genomic Aberrations

Complexity of low-frequency earthquakes activity in western Shikoku

2020 ◽  
Author(s):  
Natalia Poiata ◽  
Jean-Pierre Vilotte ◽  
Nikolai Shapiro ◽  
Mariano Supino ◽  
Kazushige Obara
Keyword(s):  
Subduction Zones ◽  
Large Scale ◽  
Active Faults ◽  
Low Frequency ◽  
Space Time ◽  
Interaction Patterns ◽  
Slow Slip Events ◽  
Time Activity ◽  
Tectonic Tremor ◽  
Slow Earthquakes

<p>Short-duration transient seismic events known as low-frequency earthquakes (LFEs) are a component of the slow earthquakes family observed in the transition zone, at the root of seismogenic regions of the subduction zones or active faults. LFEs are the signature of impulse seismic energy radiation associated to and often mixed within complex tectonic tremor signal. Detailed analysis and characterization of LFE space-time activity in relation to other slow earthquake phenomena can provide important information about the state and the processes of fault interface.</p><p>We derive a catalog of LFEs in western Shikoku (Japan) by applying a full waveform coherency-based detection and location method to the 4-year continuous data covering the period of 2013-2016 and recorded at Hi-net seismic stations of NIED. The obtained catalog of over 150,000 detected events allows looking into the details of LFE space-time activity during the tectonic tremor sequences and inter-sequence periods.</p><p>We use this catalogue of LFEs to perform a systematic statistical analysis of the event occurrence patterns by applying correlation and clustering analysis to infer the large-scale (long temporal ~ 1-2 day duration) space-time characteristics and interaction patterns of activity and its potential relation to the structural complexity of the subducting plate. We also analyze the correlation between the migration of clustered LFE activity during energetic tremor sequences and short-term slow slip events occurring in the area during the analyzed period.</p>

Cultural Interaction Patterns in the Bronze Age: Ritual Bronze Artifacts from Korea and Japan

2019 ◽  
Vol 47 (3) ◽  
pp. 68-73
Author(s):  
A. L. Nesterkina ◽  
E. A. Solovieva ◽  
I. S. Gnezdilova
Keyword(s):  
Social Status ◽  
Bronze Age ◽  
Large Scale ◽  
Distribution Center ◽  
Interaction Patterns ◽  
Cultural Interaction ◽  
Complex Construction ◽  
Korean Type ◽  
High Social Status ◽  
The Bronze Age

This study focuses on ritual bronze items that are very informative for reconstructing cultural ties and migrations between Korea and Japan in 400 BC to 300 AD. Their large-scale introduction to Korea is related to the culture of Korean-type daggers, whose distribution center was located in northwestern Korea. We give a detailed description of Bronze Age artifacts, including weapons and ritual items from that area. They occur mostly in single burials with a complex construction, possibly attesting to high social status. In Japan, Korean-type artifacts fi rst appear in northern Kyushu during the Yayoi age, in burials with wooden coffi ns and urns. The analysis of molds for casting narrow-bladed daggers, socketed spearheads, and picks suggests that Korean-type items spread from northern Kyushu. Late Yayoi ritual bronze artifacts include mostly mirrors of the Han type, evidently indicating migrations from the mainland.

scholarly journals A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Weifeng Li ◽  
Xiaoyun Cheng ◽  
Zhengyu Duan ◽  
Dongyuan Yang ◽  
Gaohua Guo
Keyword(s):  
Mobile Phone ◽  
Large Scale ◽  
Pattern Mining ◽  
Interaction Analysis ◽  
Spatial Interaction ◽  
Frequent Pattern Mining ◽  
Frequent Pattern ◽  
Mobile Phone Data ◽  
Interaction Patterns ◽  
Critical Activity

The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework.

scholarly journals Algorithms for protein interaction networks

2005 ◽  
Vol 33 (3) ◽  
pp. 530-534 ◽  
Author(s):  
M. Lappe ◽  
L. Holm
Keyword(s):  
Protein Interactions ◽  
Biological Networks ◽  
Protein Function ◽  
Large Scale ◽  
Sequence Similarity ◽  
Functional Characterization ◽  
Interaction Networks ◽  
Computational Techniques ◽  
Interaction Patterns ◽  
Main Challenge

The functional characterization of all genes and their gene products is the main challenge of the postgenomic era. Recent experimental and computational techniques have enabled the study of interactions among all proteins on a large scale. In this paper, approaches will be presented to exploit interaction information for the inference of protein structure, function, signalling pathways and ultimately entire interactomes. Interaction networks can be modelled as graphs, showing the operation of gene function in terms of protein interactions. Since the architecture of biological networks differs distinctly from random networks, these functional maps contain a signal that can be used for predictive purposes. Protein function and structure can be predicted by matching interaction patterns, without the requirement of sequence similarity. Moving on to a higher level definition of protein function, the question arises how to decompose complex networks into meaningful subsets. An algorithm will be demonstrated, which extracts whole signal-transduction pathways from noisy graphs derived from text-mining the biological literature. Finally, an algorithmic strategy is formulated that enables the proteomics community to build a reliable scaffold of the interactome in a fraction of the time compared with uncoordinated efforts.

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