Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Yan-Ni Tang"'
Autor:
Yan-Ni Tang, Ju Xiang, Yuan-Yuan Gao, Zhi-Zhong Wang, Hui-Jia Li, Shi Chen, Yan Zhang, Jian-Ming Li, Yong-Hong Tang, Yong-Jun Chen
Publikováno v:
IEEE Access, Vol 7, Pp 148814-148827 (2019)
Many methods have been proposed to detect communities/modules in various networks such as biological molecular networks and disease networks, while optimizing statistical measures for community structures is one of the most popular ways for community
Externí odkaz:
https://doaj.org/article/b962e79c8ed34d83b0db87ef3b15e781
Autor:
Shi Chen, Zhi-Zhong Wang, Liang Tang, Yan-Ni Tang, Yuan-Yuan Gao, Hui-Jia Li, Ju Xiang, Yan Zhang
Publikováno v:
PLoS ONE, Vol 13, Iss 10, p e0205284 (2018)
Community structures are ubiquitous in various complex networks, implying that the networks commonly be composed of groups of nodes with more internal links and less external links. As an important topic in network theory, community detection is of i
Externí odkaz:
https://doaj.org/article/545c128d09024d7084c7efafc99a2333
Autor:
Ju Xiang, Yongjun Chen, Yan Zhang, Shi Chen, Hui-Jia Li, Zhi-Zhong Wang, Yonghong Tang, Yan-Ni Tang, Jian-Ming Li, Yuan-Yuan Gao
Publikováno v:
IEEE Access, Vol 7, Pp 148814-148827 (2019)
Many methods have been proposed to detect communities/modules in various networks such as biological molecular networks and disease networks, while optimizing statistical measures for community structures is one of the most popular ways for community
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5abec23a2c7ac6decdb92827e3cd48a1
https://doi.org/10.1109/access.2019.2946080
https://doi.org/10.1109/access.2019.2946080
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783030678708
ADHIP (1)
ADHIP (1)
In order to improve the accuracy of the classification of the big data of disease gene detection, an algorithm for the classification of the big data of disease gene detection based on the complex network technology was proposed. On the basis of comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99b2aeab5b49bc9c7386ecde3c27a371
https://doi.org/10.1007/978-3-030-67871-5_28
https://doi.org/10.1007/978-3-030-67871-5_28
Publikováno v:
Physica A: Statistical Mechanics and its Applications. 491:693-707
Community detection is one of important issues in the research of complex networks. In literatures, many methods have been proposed to detect community structures in the networks, while they also have the scope of application themselves. In this pape
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a21915dd11277d06923f1a67aa8d4e7
https://doi.org/10.1016/j.physa.2017.09.090
https://doi.org/10.1016/j.physa.2017.09.090
Publikováno v:
Canadian Journal of Physics. 93:418-423
Detection of community structures in complex networks is a common challenge in the study of complex networks. Recently, various methods have been proposed to discover community structures at different scales. Here, the multiscale methods based on Pot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8e13f335b536199de49ed12d3e1e4f4
https://doi.org/10.1139/cjp-2013-0652
https://doi.org/10.1139/cjp-2013-0652
Publikováno v:
Pramana. 87
Many real-world networks such as the protein–protein interaction networks and metabolic networks often display nontrivial correlations between degrees of vertices connected by edges. Here, we analyse the statistical methods used usually to describe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cf0f9d994f5370a04f14b29a73513ba
https://doi.org/10.1007/s12043-016-1290-y
https://doi.org/10.1007/s12043-016-1290-y
Autor:
Hui-Jia Li, Liang Tang, Zhi-Zhong Wang, Yan Zhang, Ju Xiang, Shi Chen, Yuan-Yuan Gao, Yan-Ni Tang
Publikováno v:
PLoS ONE
PLoS ONE, Vol 13, Iss 10, p e0205284 (2018)
PLoS ONE, Vol 13, Iss 10, p e0205284 (2018)
Community structures are ubiquitous in various complex networks, implying that the networks commonly be composed of groups of nodes with more internal links and less external links. As an important topic in network theory, community detection is of i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51214485d2670ed9c8a28cff790e7f90
https://doi.org/10.1371/journal.pone.0205284
https://doi.org/10.1371/journal.pone.0205284
Community detection is of considerable importance for analyzing the structure and function of complex networks. Many real-world networks may possess community structures at multiple scales, and recently, various multi-resolution methods were proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::507d3ed824bab1df6de69d934c0c16d5
Autor:
Ju Xiang, Ke Hu, Yan Zhang, Mei-Hua Bao, Liang Tang, Yan-Ni Tang, Yuan-Yuan Gao, Jian-Ming Li, Benyan Chen, Jing-Bo Hu
Publikováno v:
Journal of Statistical Mechanics: Theory & Experiment; Mar2016, Vol. 2016 Issue 3, p1-1, 1p