scholarly journals MotifNet: a web-server for network motif analysis

2017 ◽  
Vol 33 (12) ◽  
pp. 1907-1909 ◽  
Author(s):  
Ilan Y Smoly ◽  
Eugene Lerman ◽  
Michal Ziv-Ukelson ◽  
Esti Yeger-Lotem
Keyword(s):  
Network Motif ◽  
Web Server ◽  
Motif Analysis

scholarly journals SFmap: a web server for motif analysis and prediction of splicing factor binding sites

2010 ◽  
Vol 38 (Web Server) ◽  
pp. W281-W285 ◽  
Author(s):  
I. Paz ◽  
M. Akerman ◽  
I. Dror ◽  
I. Kosti ◽  
Y. Mandel-Gutfreund
Keyword(s):  
Binding Sites ◽  
Web Server ◽  
Splicing Factor ◽  
Motif Analysis ◽  
Factor Binding

scholarly journals Burkitt lymphoma‑associated network construction and important network motif analysis

2018 ◽  
Author(s):  
Kunhao Wang ◽  
Chao Ma ◽  
Chong Xing ◽  
Chin‑Ling Chen ◽  
Zhigang Chen ◽  
...  
Keyword(s):  
Burkitt Lymphoma ◽  
Network Motif ◽  
Motif Analysis ◽  
Network Construction

scholarly journals Network motif analysis of a multi-mode genetic-interaction network

2007 ◽  
Vol 8 (8) ◽  
pp. R160 ◽  
Author(s):  
R James Taylor ◽  
Andrew F Siegel ◽  
Timothy Galitski
Keyword(s):  
Genetic Interaction ◽  
Network Motif ◽  
Interaction Network ◽  
Motif Analysis ◽  
Genetic Interaction Network ◽  
Multi Mode

scholarly journals Network Motif Analysis in Clouds - Subgraph Enumeration with Iterative Hadoop MapReduce

2016 ◽  
Vol 4 (4) ◽  
pp. 28-40
Author(s):  
Vartika Verma ◽  
◽  
Paul Park Kwon ◽  
Anand Joglekar ◽  
Wooyoung Kim
Keyword(s):  
Network Motif ◽  
Motif Analysis ◽  
Hadoop Mapreduce

scholarly journals Inter-organisational patent opposition network: how companies form adversarial relationships

2020 ◽  
Vol 72 (1) ◽  
pp. 145-166
Author(s):  
Tomomi Kito ◽  
Nagi Moriya ◽  
Junichi Yamanoi
Keyword(s):  
Network Motif ◽  
Negative Relationship ◽  
Positive Sign ◽  
Motif Analysis ◽  
Strategic Action ◽  
Foreign Companies ◽  
Industrial Sectors ◽  
Heavy Tailed ◽  
First Time ◽  
Negative Relationships

AbstractMuch of the research on networks using patent data focuses on citations and the collaboration networks of inventors, hence regarding patents as a positive sign of invention. However, patenting is, most importantly, a strategic action used by companies to compete with each other. This study sheds light on inter-organisational adversarial relationships in patenting for the first time. We constructed and analysed the network of companies connected via patent opposition relationships that occurred between 1980 and 2018. A majority of the companies are directly or indirectly connected to each other and hence form the largest connected component. We found that, in the network, many companies disapprove patents in various industrial sectors as well as those owned by foreign companies. The network exhibits heavy-tailed, power-law-like degree distribution, and assortative mixing. We further investigated the dynamics of the formation of this network by conducting a temporal network motif analysis, with patent co-ownership among the companies being considered. By regarding opposition as a negative relationship and patent co-ownership as a positive relationship, we analysed where collaboration may occur in the opposition network and how such positive relationships would interact with negative relationships. The results identified the structurally imbalanced triadic motifs and the temporal patterns of the occurrence of triads formed by a mixture of positive and negative relationships. Our findings suggest that the mechanisms of the emergence of the inter-organisational adversarial relationships may differ from those of other types of negative relationships, hence necessitating further research.

scholarly journals The network motif architecture of dominance hierarchies

2015 ◽  
Vol 12 (105) ◽  
pp. 20150080 ◽  
Author(s):  
Daizaburo Shizuka ◽  
David B. McDonald
Keyword(s):  
Network Analysis ◽  
Social Evolution ◽  
Network Motif ◽  
Motif Analysis ◽  
Social Hierarchies ◽  
Dominance Hierarchies ◽  
High Frequencies ◽  
Dominance Relations ◽  
The Past ◽  
Two Factors

The widespread existence of dominance hierarchies has been a central puzzle in social evolution, yet we lack a framework for synthesizing the vast empirical data on hierarchy structure in animal groups. We applied network motif analysis to compare the structures of dominance networks from data published over the past 80 years. Overall patterns of dominance relations, including some aspects of non-interactions, were strikingly similar across disparate group types. For example, nearly all groups exhibited high frequencies of transitive triads, whereas cycles were very rare. Moreover, pass-along triads were rare, and double-dominant triads were common in most groups. These patterns did not vary in any systematic way across taxa, study settings (captive or wild) or group size. Two factors significantly affected network motif structure: the proportion of dyads that were observed to interact and the interaction rates of the top-ranked individuals. Thus, study design (i.e. how many interactions were observed) and the behaviour of key individuals in the group could explain much of the variations we see in social hierarchies across animals. Our findings confirm the ubiquity of dominance hierarchies across all animal systems, and demonstrate that network analysis provides new avenues for comparative analyses of social hierarchies.

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