VENLO: Interactive Visual Exploration of Aligned Biological Networks and Their Evolution

2012 ◽  
pp. 229-247 ◽  
Author(s):  
Steffen Brasch ◽  
Georg Fuellen ◽  
Lars Linsen
Keyword(s):  
Biological Networks ◽  
Visual Exploration

scholarly journals CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components

2017 ◽  
Author(s):  
Henry Heberle ◽  
Marcelo Falsarella Carazzolle ◽  
Guilherme P. Telles ◽  
Gabriela Vaz Meirelles ◽  
Rosane Minghim
Keyword(s):  
Biological Networks ◽  
Visual Exploration ◽  
Web Tool ◽  
Biomolecular Interaction ◽  
Dense Networks ◽  
A Cell ◽  
Visualization Of Data ◽  
Cellular Compartments ◽  
Cellular Components ◽  
Dynamic Investigation

AbstractBackgroundThe advent of “omics” science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability.ResultsHere we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB.ConclusionsCellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

scholarly journals FluxMap: A VANTED add-on for the visual exploration of flux distributions in biological networks

2012 ◽  
Vol 6 (1) ◽  
pp. 33 ◽  
Author(s):  
Hendrik Rohn ◽  
Anja Hartmann ◽  
Astrid Junker ◽  
Björn H Junker ◽  
Falk Schreiber
Keyword(s):  
Biological Networks ◽  
Visual Exploration

scholarly journals VANLO - Interactive visual exploration of aligned biological networks

2009 ◽  
Vol 10 (1) ◽  
pp. 327 ◽  
Author(s):  
Steffen Brasch ◽  
Lars Linsen ◽  
Georg Fuellen
Keyword(s):  
Biological Networks ◽  
Visual Exploration

The Gender Typicality of Faces and Its Impact on Visual Processing and on Hiring Decisions

2013 ◽  
Vol 60 (6) ◽  
pp. 444-452 ◽  
Author(s):  
Lisa von Stockhausen ◽  
Sara Koeser ◽  
Sabine Sczesny
Keyword(s):  
Visual Processing ◽  
Past Research ◽  
Visual Exploration ◽  
Facial Appearance ◽  
Leadership Roles ◽  
Hiring Decisions ◽  
Leadership Selection ◽  
Gender Typicality ◽  
Second Stage ◽  
The Feminine

Past research has shown that the gender typicality of applicants’ faces affects leadership selection irrespective of a candidate’s gender: A masculine facial appearance is congruent with masculine-typed leadership roles, thus masculine-looking applicants are hired more certainly than feminine-looking ones. In the present study, we extended this line of research by investigating hiring decisions for both masculine- and feminine-typed professional roles. Furthermore, we used eye tracking to examine the visual exploration of applicants’ portraits. Our results indicate that masculine-looking applicants were favored for the masculine-typed role (leader) and feminine-looking applicants for the feminine-typed role (team member). Eye movement patterns showed that information about gender category and facial appearance was integrated during first fixations of the portraits. Hiring decisions, however, were not based on this initial analysis, but occurred at a second stage, when the portrait was viewed in the context of considering the applicant for a specific job.

Visual exploration of dynamic real-world scenes in patients with hemispatial neglect

2011 ◽  
Vol 42 (01) ◽  
Author(s):  
J. von der Gablentz ◽  
A. Sprenger ◽  
M. Dorr ◽  
E. Barth ◽  
W. Heide ◽  
...  
Keyword(s):  
Real World ◽  
Visual Exploration ◽  
Hemispatial Neglect

Analysis of Protein-Protein Interaction Networks through Computational Approaches

2020 ◽  
Vol 27 (4) ◽  
pp. 265-278 ◽  
Author(s):  
Ying Han ◽  
Liang Cheng ◽  
Weiju Sun
Keyword(s):  
Protein Interaction ◽  
Biological Networks ◽  
Interaction Networks ◽  
Computational Techniques ◽  
Cellular Functions ◽  
Protein Protein Interaction ◽  
Comprehensive Information ◽  
Protein Interaction Prediction ◽  
Or Gene ◽  
Experimental Findings

The interactions among proteins and genes are extremely important for cellular functions. Molecular interactions at protein or gene levels can be used to construct interaction networks in which the interacting species are categorized based on direct interactions or functional similarities. Compared with the limited experimental techniques, various computational tools make it possible to analyze, filter, and combine the interaction data to get comprehensive information about the biological pathways. By the efficient way of integrating experimental findings in discovering PPIs and computational techniques for prediction, the researchers have been able to gain many valuable data on PPIs, including some advanced databases. Moreover, many useful tools and visualization programs enable the researchers to establish, annotate, and analyze biological networks. We here review and list the computational methods, databases, and tools for protein−protein interaction prediction.

Algorithmic and Stochastic Representations of Gene Regulatory Networks and Protein-Protein Interactions

2019 ◽  
Vol 19 (6) ◽  
pp. 413-425 ◽  
Author(s):  
Athanasios Alexiou ◽  
Stylianos Chatzichronis ◽  
Asma Perveen ◽  
Abdul Hafeez ◽  
Ghulam Md. Ashraf
Keyword(s):  
Protein Interactions ◽  
Biological Networks ◽  
Regulatory Networks ◽  
Review Paper ◽  
Boolean Networks ◽  
Diagnostic Tools ◽  
Complex Nature ◽  
Cellular Interactions ◽  
Protein Protein Interactions ◽  
Deterministic Models

Background:Latest studies reveal the importance of Protein-Protein interactions on physiologic functions and biological structures. Several stochastic and algorithmic methods have been published until now, for the modeling of the complex nature of the biological systems.Objective:Biological Networks computational modeling is still a challenging task. The formulation of the complex cellular interactions is a research field of great interest. In this review paper, several computational methods for the modeling of GRN and PPI are presented analytically.Methods:Several well-known GRN and PPI models are presented and discussed in this review study such as: Graphs representation, Boolean Networks, Generalized Logical Networks, Bayesian Networks, Relevance Networks, Graphical Gaussian models, Weight Matrices, Reverse Engineering Approach, Evolutionary Algorithms, Forward Modeling Approach, Deterministic models, Static models, Hybrid models, Stochastic models, Petri Nets, BioAmbients calculus and Differential Equations.Results:GRN and PPI methods have been already applied in various clinical processes with potential positive results, establishing promising diagnostic tools.Conclusion:In literature many stochastic algorithms are focused in the simulation, analysis and visualization of the various biological networks and their dynamics interactions, which are referred and described in depth in this review paper.

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