Tulip 5

Auber, David; Archambault, Daniel; Bourqui, Romain; Delest, Maylis; Dubois, Jonathan; Lambert, Antoine; Mary, Patrick; Mathiaut, Morgan; Mélançon, Guy; Pinaud, Bruno; Renoust, Benjamin; Vallet, Jason

doi:10.1007/978-1-4614-7163-9_315-1

Cited by 37 publications

(23 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The NetworkX library (Hagberg et al 2008) is prevalent for the Python environment, while the igraph library (Nepusz and Csárdi 2006) is commonly used among the R users. C, and C++ alternatives include SNAP (Leskovec and Sosič 2016), Boost Graph Library (BGL) (The Boost Graph Library 2002), and Tulip (Auber 2004;Auber et al 2017). Compared to GUI-based analysis, APIbased approaches result in a series of high-level function calls, which generate the desired output.…”

Section: Related Workmentioning

confidence: 99%

“…This paper significantly extends the work on multilayer network visualization and analysis presented in our previous conference publication (Škrlj et al 2019). First, the related work section ("Related work" section) has been extended by including tools Pajek (Batagelj and Mrvar 2001) and Tulip (Auber 2004;Auber et al 2017) that inspired the creation of Py3plex. Next, we extended the description of the library's features ("Key features" section).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Py3plex toolkit for visualization and analysis of multilayer networks

2019

View full text Add to dashboard Cite

Complex networks are used as means for representing multimodal, real-life systems. With increasing amounts of data that lead to large multilayer networks consisting of different node and edge types, that can also be subject to temporal change, there is an increasing need for versatile visualization and analysis software. This work presents a lightweight Python library, Py3plex, which focuses on the visualization and analysis of multilayer networks. The library implements a set of simple graphical primitives supporting intra-as well as inter-layer visualization. It also supports many common operations on multilayer networks, such as aggregation, slicing, indexing, traversal, and more. The paper also focuses on how node embeddings can be used to speed up contemporary (multilayer) layout computation. The library's functionality is showcased on both real and synthetic networks.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Py3plex toolkit for visualization and analysis of multilayer networks

2019

View full text Add to dashboard Cite

show abstract

“…MDS-like approaches to drawing graphs are exemplified in algorithms such as that of Kamada-Kawai [19], Koren and Carmel [25]. Most commonly used graph drawing systems, such as Graphviz [13], Pajek [5], Tulip [2] and Gephi [4], provide options to visualize graphs in 3D based on MDS-like optimization. Variants of MDS are used in many graph layout systems, including [10,15,30,37].…”

Section: Previous Workmentioning

confidence: 99%

Multi-Perspective, Simultaneous Embedding

Hossain¹,

Huroyan²,

Kobourov³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…force-directed, hierarchical, orthogonal and spectral) to generate informative and appealing 2D/3D views thus minimizing any possible node overlaps and connection crossovers (3). Among a decent variety of applications today (4, 5), widely-used interactive 2D visualizers include the Cytoscape (6), Cytoscape.js (7), String (8), NORMA (9), Gephi (10), Pajek (11) and Tulip (12) whereas successful 3D visualizers include the Graphia (Kajeka) and BioLayout Express (13).…”

Section: Introductionmentioning

confidence: 99%

Arena3D^web: Interactive 3D visualization of multilayered networks

Karatzas

Baltoumas

Panayiotou

et al. 2020

Preprint

View full text Add to dashboard Cite

Efficient integration and visualization of heterogeneous biomedical information in a single view is a key challenge. In this study, we present Arena3Dweb, the first, fully interactive and dependency-free, web application which allows the visualization of multilayered graphs in 3D space. With Arena3Dweb, users can integrate multiple networks in a single view along with their intra- and inter-layer connections. For clearer and more informative views, users can choose between a plethora of layout algorithms and apply them on a set of selected layers either individually or in combination. Users can align networks and highlight node topological features, whereas each layer as well as the whole scene can be translated, rotated and scaled in 3D space. User-selected edge colors can be used to highlight important paths, while node positioning, coloring and resizing can be adjusted on-the-fly. In its current version, Arena3Dweb supports weighted and unweighted undirected graphs and is written in R, Shiny and JavaScript. We demonstrate the functionality of Arena3Dweb using two different use-case scenarios; one regarding drug repurposing for SARS-CoV-2 and one related to GPCR signaling pathways implicated in melanoma. Arena3Dweb is available at http://bib.fleming.gr:3838/Arena3D.

show abstract

Tulip 5

Cited by 37 publications

References 43 publications

Py3plex toolkit for visualization and analysis of multilayer networks

Py3plex toolkit for visualization and analysis of multilayer networks

Multi-Perspective, Simultaneous Embedding

Arena3D^web: Interactive 3D visualization of multilayered networks

Contact Info

Product

Resources

About

Tulip 5

Cited by 37 publications

References 43 publications

Py3plex toolkit for visualization and analysis of multilayer networks

Py3plex toolkit for visualization and analysis of multilayer networks

Multi-Perspective, Simultaneous Embedding

Arena3Dweb: Interactive 3D visualization of multilayered networks

Contact Info

Product

Resources

About

Arena3D^web: Interactive 3D visualization of multilayered networks