scholarly journals Hidden Topological Structure of Flow Network Functionality

2021 ◽  
Vol 126 (2) ◽  
Author(s):  
Jason W. Rocks ◽  
Andrea J. Liu ◽  
Eleni Katifori
Keyword(s):  
Topological Structure ◽  
Flow Network ◽  
Structure Of Flow ◽  
Network Functionality

Uncovering Atherosclerotic Risk Disease Gene Based on Expression and Network Topological Structure*

2010 ◽  
Vol 37 (8) ◽  
pp. 916-922
Author(s):  
Hong WANG ◽  
Xiao-Li QU ◽  
Yan ZHAO ◽  
Jing ZHANG ◽  
Li-Na CHEN
Keyword(s):  
Topological Structure ◽  
Disease Gene

Brief Survey of Biological Network Alignment and a Variant with Incorporation of Functional Annotations

2018 ◽  
Vol 14 (1) ◽  
pp. 4-10
Author(s):  
Fang Jing ◽  
Shao-Wu Zhang ◽  
Shihua Zhang
Keyword(s):  
Gene Ontology ◽  
Topological Structure ◽  
Metabolic Networks ◽  
Biological Network ◽  
Genomic Sequence ◽  
Network Alignment ◽  
Future Directions ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks

Background:Biological network alignment has been widely studied in the context of protein-protein interaction (PPI) networks, metabolic networks and others in bioinformatics. The topological structure of networks and genomic sequence are generally used by existing methods for achieving this task.Objective and Method:Here we briefly survey the methods generally used for this task and introduce a variant with incorporation of functional annotations based on similarity in Gene Ontology (GO). Making full use of GO information is beneficial to provide insights into precise biological network alignment.Results and Conclusion:We analyze the effect of incorporation of GO information to network alignment. Finally, we make a brief summary and discuss future directions about this topic.

Information on evolutionary age in redundancy of complex network

2019 ◽  
Vol 33 (27) ◽  
pp. 1950331
Author(s):  
Shiguo Deng ◽  
Henggang Ren ◽  
Tongfeng Weng ◽  
Changgui Gu ◽  
Huijie Yang
Keyword(s):  
Principal Component Analysis ◽  
Complex Networks ◽  
Metabolic Network ◽  
Complex Network ◽  
Cellular Networks ◽  
Topological Structure ◽  
Quantitative Measure ◽  
Principal Component ◽  
Evolutionary Information ◽  
Local Patterns

Evolutionary processes of many complex networks in reality are dominated by duplication and divergence. This mechanism leads to redundant structures, i.e. some nodes share most of their neighbors and some local patterns are similar, called redundancy of network. An interesting reverse problem is to discover evolutionary information from the present topological structure. We propose a quantitative measure of redundancy of network from the perspective of principal component analysis. The redundancy of a community in the empirical human metabolic network is negatively and closely related with its evolutionary age, which is consistent with that for the communities in the modeling protein–protein network. This behavior can be used to find the evolutionary difference stored in cellular networks.

scholarly journals Topological Structure of Vortex Solution in Jackiw–Pi Model

2007 ◽  
Vol 48 (1) ◽  
pp. 143-146 ◽  
Author(s):  
Li Xi-Guo ◽  
Liu Zi-Yu ◽  
Li Yong-Qing ◽  
Gao Yuan ◽  
Guo Yan-Rui ◽  
...  
Keyword(s):  
Topological Structure ◽  
Vortex Solution

The impact of China's import ban on global copper scrap flow network and the domestic copper sustainability

2021 ◽  
Vol 169 ◽  
pp. 105525
Author(s):  
Sen Liu ◽  
Wei Liu ◽  
Quanyin Tan ◽  
Jinhui Li ◽  
Wenqing Qin ◽  
...  
Keyword(s):  
Flow Network ◽  
The Impact

scholarly journals Modifications in the Topological Structure of EEG Functional Connectivity Networks during Listening Tonal and Atonal Concert Music in Musicians and Non-Musicians

2021 ◽  
Vol 11 (2) ◽  
pp. 159
Author(s):  
Almudena González ◽  
Manuel Santapau ◽  
Antoni Gamundí ◽  
Ernesto Pereda ◽  
Julián J. González
Keyword(s):  
Topological Structure ◽  
Phase Synchronization ◽  
Random Network ◽  
Small World ◽  
Surrogate Data ◽  
Musical Structure ◽  
Beta Band ◽  
Tonal Music ◽  
Frequency Bands ◽  
Concert Music

The present work aims to demonstrate the hypothesis that atonal music modifies the topological structure of electroencephalographic (EEG) connectivity networks in relation to tonal music. To this, EEG monopolar records were taken in musicians and non-musicians while listening to tonal, atonal, and pink noise sound excerpts. EEG functional connectivities (FC) among channels assessed by a phase synchronization index previously thresholded using surrogate data test were computed. Sound effects, on the topological structure of graph-based networks assembled with the EEG-FCs at different frequency-bands, were analyzed throughout graph metric and network-based statistic (NBS). Local and global efficiency normalized (vs. random-network) measurements (NLE|NGE) assessing network information exchanges were able to discriminate both music styles irrespective of groups and frequency-bands. During tonal audition, NLE and NGE values in the beta-band network get close to that of a small-world network, while during atonal and even more during noise its structure moved away from small-world. These effects were attributed to the different timbre characteristics (sounds spectral centroid and entropy) and different musical structure. Results from networks topographic maps for strength and NLE of the nodes, and for FC subnets obtained from the NBS, allowed discriminating the musical styles and verifying the different strength, NLE, and FC of musicians compared to non-musicians.

A MODIFIED GENERALIZED LORENZ-TYPE SYSTEM AND ITS CANONICAL FORM

2009 ◽  
Vol 19 (06) ◽  
pp. 1931-1949 ◽  
Author(s):  
QIGUI YANG ◽  
KANGMING ZHANG ◽  
GUANRONG CHEN
Keyword(s):  
Special Form ◽  
Topological Structure ◽  
Complex Dynamics ◽  
Type System ◽  
Chaotic Attractors ◽  
Hopf Bifurcations ◽  
Compound Structure ◽  
Two Parameters ◽  
First Time ◽  
New System

In this paper, a modified generalized Lorenz-type system is introduced, which is state-equivalent to a simple and special form, and is parameterized by two parameters useful for chaos turning and system classification. More importantly, based on the parameterized form, two classes of new chaotic attractors are found for the first time in the literature, which are similar but nonequivalent in topological structure. To further understand the complex dynamics of the new system, some basic properties such as Lyapunov exponents, Hopf bifurcations and compound structure of the attractors are analyzed and demonstrated with careful numerical simulations.

Sign in / Sign up

Export Citation Format

Share Document