scholarly journals The Network Analysis Profiler (NAP v2.0): a web tool for visual topological comparison between multiple networks

2021 ◽  
Vol 26 (1) ◽  
pp. e943
Author(s):  
Mikaela Koutrouli ◽  
Theodosios Theodosiou ◽  
Ioannis Iliopoulos ◽  
Georgios A. Pavlopoulos
Keyword(s):  
Network Analysis ◽  
Bipartite Graphs ◽  
Web Tool ◽  
Venn Diagrams ◽  
Multiple Networks ◽  
Topological Features ◽  
3D Network ◽  
Edge Based ◽  
2D And 3D ◽  
Scatterplot Matrix

In this article we present the Network Analysis Profiler (NAP v2.0), a web tool to directly compare the topological features of multiple networks simultaneously. NAP is written in R and Shiny and currently offers both 2D and 3D network visualisation, as well as simultaneous visual comparisons of node- and edge-based topological features as bar charts or scatterplot matrix. NAP is fully interactive, and users can easily export and visualise the intersection between any pair of networks using Venn diagrams or a 2D and a 3D multi-layer graph-based visualisation. NAP supports weighted, unweighted, directed, undirected and bipartite graphs.

scholarly journals The Network Analysis Profiler (NAP v2.0): a web tool for visual topological comparison between multiple networks

2021 ◽  
Vol 26 ◽  
pp. e943
Author(s):  
Mikaela Koutrouli ◽  
Theodosios Theodosiou ◽  
Ioannis Iliopoulos ◽  
Georgios A. Pavlopoulos
Keyword(s):  
Network Analysis ◽  
Bipartite Graphs ◽  
Web Tool ◽  
Venn Diagrams ◽  
Multiple Networks ◽  
Topological Features ◽  
3D Network ◽  
Edge Based ◽  
2D And 3D ◽  
Scatterplot Matrix

In this article we present the Network Analysis Profiler (NAP v2.0), a web tool to directly compare the topological features of multiple networks simultaneously. NAP is written in R and Shiny and currently offers both 2D and 3D network visualisation, as well as simultaneous visual comparisons of node- and edge-based topological features as bar charts or scatterplot matrix. NAP is fully interactive, and users can easily export and visualise the intersection between any pair of networks using Venn diagrams or a 2D and a 3D multi-layer graph-based visualisation. NAP supports weighted, unweighted, directed, undirected and bipartite graphs.

scholarly journals The Network Analysis Profiler (NAP v2.0): A web tool for visual topological comparison between multiple networks

2020 ◽  
Author(s):  
Mikaela Koutrouli ◽  
Theodosios Theodosiou ◽  
Ioannis Iliopoulos ◽  
Georgios A. Pavlopoulos
Keyword(s):  
Network Analysis ◽  
Web Tool ◽  
Venn Diagrams ◽  
Multiple Networks ◽  
Link Type ◽  
Topological Features ◽  
3D Network ◽  
Edge Based ◽  
2D And 3D ◽  
Scatterplot Matrix

ABSTRACTIn this article we present the Network Analysis Profiler (NAP v2.0), a web tool to directly compare the topological features of multiple networks simultaneously. NAP is written in R and Shiny and currently offers both 2D and 3D network visualization as well as simultaneous visual comparisons of node- and edge-based topological features both as bar charts or as a scatterplot matrix. NAP is fully interactive and users can easily export and visualize the intersection between any pair of networks using Venn diagrams or a 2D and a 3D multi-layer graph-based visualization. NAP supports weighted, unweighted, directed, undirected and bipartite graphs and is available at: http://bib.fleming.gr:3838/NAP/. Its code can be found at: https://github.com/PavlopoulosLab/NAP

scholarly journals What do we see when we look at networks: Visual network analysis, relational ambiguity, and force-directed layouts

2021 ◽  
Vol 8 (1) ◽  
pp. 205395172110184
Author(s):  
Tommaso Venturini ◽  
Mathieu Jacomy ◽  
Pablo Jensen
Keyword(s):  
Social Sciences ◽  
Network Analysis ◽  
Dimensional Space ◽  
Two Dimensional ◽  
Project Networks ◽  
Topological Features ◽  
Exploratory Data ◽  
Inherent Ambiguity ◽  
Visual Network ◽  
Visual Ambiguity

It is increasingly common in natural and social sciences to rely on network visualizations to explore relational datasets and illustrate findings. Such practices have been around long enough to prove that scholars find it useful to project networks in a two-dimensional space and to use their visual qualities as proxies for their topological features. Yet these practices remain based on intuition, and the foundations and limits of this type of exploration are still implicit. To fill this lack of formalization, this paper offers explicit documentation for the kind of visual network analysis encouraged by force-directed layouts. Using the example of a network of Jazz performers, band and record labels extracted from Wikipedia, the paper provides guidelines on how to make networks readable and how to interpret their visual features. It discusses how the inherent ambiguity of network visualizations can be exploited for exploratory data analysis. Acknowledging that vagueness is a feature of many relational datasets in the humanities and social sciences, the paper contends that visual ambiguity, if properly interpreted, can be an asset for the analysis. Finally, we propose two attempts to distinguish the ambiguity inherited from the represented phenomenon from the distortions coming from fitting a multidimensional object in a two-dimensional space. We discuss why these attempts are only partially successful, and we propose further steps towards a metric of spatialization quality.

Designing 2D and 3D Network-on-Chip Architectures

2014 ◽  
Author(s):  
Konstantinos Tatas ◽  
Kostas Siozios ◽  
Dimitrios Soudris ◽  
Axel Jantsch
Keyword(s):  
Network On Chip ◽  
3D Network ◽  
On Chip ◽  
2D And 3D

The role of the geoid in one-, two-, and three-dimensional network adjustments

CISM journal ◽  
1990 ◽  
Vol 44 (1) ◽  
pp. 9-18 ◽  
Author(s):  
Michael G. Sideris
Keyword(s):  
Three Dimensional ◽  
One Dimensional ◽  
Control Networks ◽  
Deflections Of The Vertical ◽  
Dimensional Network ◽  
3D Network ◽  
Computational Procedures ◽  
The One ◽  
2D And 3D

The geoid and its horizontal derivatives, the deflections of the vertical, play an important role in the adjustment of geodetic networks. In the one-dimensional (1D) case, represented typically by networks of orthometric heights, the geoid provides the reference surface for the measurements. In the two-dimensional (2D) adjustment of horizontal control networks, the geoidal undulations N and deflections of the vertical ξ, η are needed for the reduction of the measured quantities onto the reference ellipsoid. In the three-dimensional (3D) adjustment, N and ξ, η are basically required to relate geodetic and astronomic quantities. The paper presents the major gravimetric methods currently used for predicting ξ, η and N, and briefly intercompares them in terms of accuracy, efficiency, and data required. The effects of N, ξ, η on various quantities used in the ID, 2D, and 3D network adjustments are described explicitly for each case and formulas are given for the errors introduced by either neglecting or using erroneous N, ξ, η in the computational procedures.

Automatic Pharynx Segmentation from MRI Data for Analysis of Sleep Related Disorders

2015 ◽  
Vol 24 (04) ◽  
pp. 1550018 ◽  
Author(s):  
Tatyana Ivanovska ◽  
René Laqua ◽  
Muhammad Laiq Shahid ◽  
Lars Linsen ◽  
Katrin Hegenscheid ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Automatic Extraction ◽  
Data Sets ◽  
Connected Component ◽  
Resonance Imaging ◽  
The Third ◽  
General Rules ◽  
Magnetic Resonance Imaging Mri ◽  
Edge Based ◽  
2D And 3D

In our project, we analyse throat structures using magnetic resonance imaging (MRI) to associate anatomic risk factors with sleep related disorders. Pharynx segmentation is the first step in the three-dimensional analysis of throat tissues.We present a pipeline for automatic pharynx segmentation. The automatic part of the approach consists of three steps: smoothing, thresholding, 2D and 3D connected component analysis. Whereas two first steps are rather common, the third step provides a set of general rules for the automatic extraction of the pharyngeal component. Our method requires less than one minute to extract the pharyngeal structures. The approach is evaluated quantitatively on 30 data sets using region-based and edge-based measures.

scholarly journals NAP: The Network Analysis Profiler, a web tool for easier topological analysis and comparison of medium-scale biological networks

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Theodosios Theodosiou ◽  
Georgios Efstathiou ◽  
Nikolas Papanikolaou ◽  
Nikos C. Kyrpides ◽  
Pantelis G. Bagos ◽  
...  
Keyword(s):  
Network Analysis ◽  
Biological Networks ◽  
Topological Analysis ◽  
Web Tool ◽  
Medium Scale
Sign in / Sign up

Export Citation Format

Share Document