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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1932 1
1958 2
1965 2
1966 1
1967 1
1968 1
1969 2
1970 4
1971 3
1972 2
1973 4
1974 2
1975 9
1976 13
1977 12
1978 15
1979 17
1980 24
1981 19
1982 30
1983 45
1984 46
1985 50
1986 62
1987 60
1988 79
1989 107
1990 116
1991 141
1992 174
1993 218
1994 247
1995 294
1996 326
1997 342
1998 415
1999 430
2000 459
2001 599
2002 688
2003 834
2004 1037
2005 1170
2006 1459
2007 1686
2008 1923
2009 2350
2010 2622
2011 2967
2012 3377
2013 3755
2014 4587
2015 5190
2016 5774
2017 6320
2018 7309
2019 8510
2020 10226
2021 13019
2022 15246
2023 15081
2024 6662

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Search Results

113,035 results

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Page 1
Network morphospace.
Avena-Koenigsberger A, Goñi J, Solé R, Sporns O. Avena-Koenigsberger A, et al. J R Soc Interface. 2015 Feb 6;12(103):20140881. doi: 10.1098/rsif.2014.0881. J R Soc Interface. 2015. PMID: 25540237 Free PMC article. Review.
The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. ...Here, we explore a new theoretical concept that lies at the intersec …
The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of …
Network meta-analysis of multicomponent interventions.
Rücker G, Petropoulou M, Schwarzer G. Rücker G, et al. Biom J. 2020 May;62(3):808-821. doi: 10.1002/bimj.201800167. Epub 2019 Apr 25. Biom J. 2020. PMID: 31021449 Free PMC article.
In network meta-analysis (NMA), treatments can be complex interventions, for example, some treatments may be combinations of others or of common components. In standard NMA, all existing (single or combined) treatments are different nodes in the network …
In network meta-analysis (NMA), treatments can be complex interventions, for example, some treatments may be combinations of o …
Graph kernels combined with the neural network on protein classification.
Qiangrong J, Guang Q. Qiangrong J, et al. J Bioinform Comput Biol. 2019 Oct;17(5):1950030. doi: 10.1142/S0219720019500306. J Bioinform Comput Biol. 2019. PMID: 31856667
In this paper, we propose a novel graph kernel named vertex-edge similarity kernel (VES kernel) based on mixed matrix, the innovation point of which is taking the adjacency matrix of the graph as the sample vector of each vertex and calculating kernel values by finding the most s …
In this paper, we propose a novel graph kernel named vertex-edge similarity kernel (VES kernel) based on mixed matrix, the innovation point …
Collective minds: social network topology shapes collective cognition.
Momennejad I. Momennejad I. Philos Trans R Soc Lond B Biol Sci. 2022 Jan 31;377(1843):20200315. doi: 10.1098/rstb.2020.0315. Epub 2021 Dec 13. Philos Trans R Soc Lond B Biol Sci. 2022. PMID: 34894735 Free PMC article. Review.
Here, we review research that combines network structure with psychological and neural experiments and modelling to understand how the topology of social networks shapes collective cognition. ...Finally, we discuss recent machine learning approaches to collec …
Here, we review research that combines network structure with psychological and neural experiments and modelling to understand …
Emergence of dynamic properties in network hypermotifs.
Adler M, Medzhitov R. Adler M, et al. Proc Natl Acad Sci U S A. 2022 Aug 9;119(32):e2204967119. doi: 10.1073/pnas.2204967119. Epub 2022 Aug 1. Proc Natl Acad Sci U S A. 2022. PMID: 35914142 Free PMC article.
Here, we develop a framework to explore the mesoscale-level behavior of complex networks. Considering network motifs as hypernodes, we define the rules for their interaction at the network's next level of organization. ...This framework provides a basi …
Here, we develop a framework to explore the mesoscale-level behavior of complex networks. Considering network motifs as hypern …
Motif Graph Neural Network.
Chen X, Cai R, Fang Y, Wu M, Li Z, Hao Z. Chen X, et al. IEEE Trans Neural Netw Learn Syst. 2023 Jun 19;PP. doi: 10.1109/TNNLS.2023.3281716. Online ahead of print. IEEE Trans Neural Netw Learn Syst. 2023. PMID: 37335782
These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph representations. Graph neural networks (GNNs) are currently the most popular model in graph embedding approaches. ...Finally, MGNN performs th …
These applications can often be cast into standard graph learning tasks, in which a crucial step is to learn low-dimensional graph represent …
Construction of a gene-gene interaction network with a combined score across multiple approaches.
Zhang AM, Song H, Shen YH, Liu Y. Zhang AM, et al. Genet Mol Res. 2015 Jun 26;14(2):7018-30. doi: 10.4238/2015.June.26.11. Genet Mol Res. 2015. PMID: 26125911 Free article.
Here, a combined network based on gene pairs with an extra layer of re-liability was constructed after converting and combining the gene pair scores using a novel algorithm across multiple approaches. ...The values of topological parameters, such as clusterin …
Here, a combined network based on gene pairs with an extra layer of re-liability was constructed after converting and combi …
Social Network Analytics for Supervised Fraud Detection in Insurance.
Óskarsdóttir M, Ahmed W, Antonio K, Baesens B, Dendievel R, Donas T, Reynkens T. Óskarsdóttir M, et al. Risk Anal. 2022 Aug;42(8):1872-1890. doi: 10.1111/risa.13693. Epub 2021 Feb 6. Risk Anal. 2022. PMID: 33547691
Finally, we combine these network features with the claim-specific features and build a supervised model with fraud in motor insurance as the target variable. ...Combining network and claim-specific features further improves the performance of supervis …
Finally, we combine these network features with the claim-specific features and build a supervised model with fraud in motor i …
Social network structure and combating social disconnection: Implications for physical health.
Farrell AK, Stanton SCE, Marshall EM. Farrell AK, et al. Curr Opin Psychol. 2022 Jun;45:101313. doi: 10.1016/j.copsyc.2022.101313. Epub 2022 Feb 25. Curr Opin Psychol. 2022. PMID: 35338892 Review.
Disconnection from one's social network has detrimental links to physical health outcomes, and there has been increased interest in treating social disconnection as a public health issue. ...In this article, we discuss the importance of combining these perspectives …
Disconnection from one's social network has detrimental links to physical health outcomes, and there has been increased interest in t …
Characteristics of the ineffective social support network: integrative review.
França MS, Lopes MVO, Frazão CMFQ, Guedes TG, Linhares FMP, Pontes CM. França MS, et al. Rev Gaucha Enferm. 2018 Oct 22;39:e20170303. doi: 10.1590/1983-1447.2018.20170303. Rev Gaucha Enferm. 2018. PMID: 30365757 Free article. Review. English, Portuguese.
OBJECTIVE: To evaluate the characteristics of the ineffective social support network evidenced in its structure, functionality and dynamics. METHOD: Integrative review, carried out in December 2017, in the bases Scopus, CINAHL, Web of Science, CUIDEN, BDENF, Lilacs and Sci …
OBJECTIVE: To evaluate the characteristics of the ineffective social support network evidenced in its structure, functionality and dy …
113,035 results
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