scholarly journals PetriScape - A plugin for discrete Petri net simulations in Cytoscape

2016 ◽  
Vol 13 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Diogo Almeida ◽  
Vasco Azevedo ◽  
Artur Silva ◽  
Jan Baumbach
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Biological Networks ◽  
Computational Analysis ◽  
Biological Network ◽  
Global Network ◽  
Data Sets ◽  
Biological Network Analysis ◽  
Network Properties ◽  
Sbml Format

SummarySystems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

scholarly journals An Improved Method for Completely Uncertain Biological Network Alignment

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Shen ◽  
Muwei Zhao ◽  
Wei Zhong ◽  
Jieyue He
Keyword(s):  
Biological Networks ◽  
Biological Network ◽  
Evaluation Criteria ◽  
Network Alignment ◽  
Global Network ◽  
Uncertain Information ◽  
Improved Method ◽  
Network Comparison ◽  
Probabilistic Network ◽  
Alignment Problem

With the continuous development of biological experiment technology, more and more data related to uncertain biological networks needs to be analyzed. However, most of current alignment methods are designed for the deterministic biological network. Only a few can solve the probabilistic network alignment problem. However, these approaches only use the part of probabilistic data in the original networks allowing only one of the two networks to be probabilistic. To overcome the weakness of current approaches, an improved method called completely probabilistic biological network comparison alignment (C_PBNA) is proposed in this paper. This new method is designed for complete probabilistic biological network alignment based on probabilistic biological network alignment (PBNA) in order to take full advantage of the uncertain information of biological network. The degree of consistency (agreement) indicates that C_PBNA can find the results neglected by PBNA algorithm. Furthermore, the GO consistency (GOC) and global network alignment score (GNAS) have been selected as evaluation criteria, and all of them proved that C_PBNA can obtain more biologically significant results than those of PBNA algorithm.

Petri Net representations in systems biology

2003 ◽  
Vol 31 (6) ◽  
pp. 1513-1515 ◽  
Author(s):  
J.W. Pinney ◽  
D.R. Westhead ◽  
G.A. McConkey
Keyword(s):  
Quantitative Analysis ◽  
Systems Biology ◽  
Petri Nets ◽  
Petri Net ◽  
Biological Networks ◽  
Research Effort ◽  
Research Directions ◽  
Mathematical Structures ◽  
New Research

The mathematical structures known as Petri Nets have recently become the focus of much research effort in both the structural and quantitative analysis of all kinds of biological networks. This review provides a very brief summary of these interesting new research directions.

scholarly journals CRISPR-based editing reveals edge-specific effects in biological networks

2018 ◽  
Author(s):  
Yi Li ◽  
Chance M. Nowak ◽  
Daniel Withers ◽  
Alexander Pertsemlidis ◽  
Leonidas Bleris
Keyword(s):  
Biological Networks ◽  
Biological Network ◽  
Cellular Survival ◽  
Specific Effects ◽  
Biological Network Analysis ◽  
Multiple Edges ◽  
Cellular Phenotypes ◽  
Microrna Pathway ◽  
The Impact

AbstractUnraveling the properties of biological networks is central to understanding normal and disease cellular phenotypes. Networks consist of functional elements (nodes) that form a variety of diverse connections (edges) with each node being a hub for multiple edges. Herein, in contrast to node-centric network perturbation and analysis approaches, we present a high-throughput CRISPR-based methodology for delineating the role of network edges. Ablation of network edges using a library targeting 93 miRNA target sites in 71 genes reveals numerous edges that control, with variable importance, cellular survival under stress. To compare the impact of removing nodes versus edges in a biological network, we dissect a specific p53-microRNA pathway. In summary, we demonstrate that network edges are critical to the function and stability of biological networks. Our results introduce a novel genetic screening opportunity via edge ablation and highlight a new dimension in biological network analysis.

scholarly journals Biological network analysis and comparison: mining new biological knowledge

2011 ◽  
Vol 1 (2) ◽  
Author(s):  
Valeria Fionda
Keyword(s):  
Life Cycle ◽  
Network Analysis ◽  
Biological Networks ◽  
Biological Network ◽  
Biological Knowledge ◽  
Biological Network Analysis ◽  
Cell Life ◽  
The World ◽  
Automated Tools

AbstractThe mechanisms underlying life machinery are still not completely understood. Something is known, something is “probably” known, other things are still unknown. Scientists all over the world are working very hard to clarify the processes regulating the cell life cycle and bioinformaticians try to support them by developing specialized automated tools. Within the plethora of applications devoted to the study of life mechanisms, tools for the analysis and comparison of biological networks are catching the attention of many researchers. It is interesting to investigate why.

scholarly journals Biological network analysis with CentiScaPe: centralities and experimental dataset integration

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 139 ◽  
Author(s):  
Giovanni Scardoni ◽  
Gabriele Tosadori ◽  
Mohammed Faizan ◽  
Fausto Spoto ◽  
Franco Fabbri ◽  
...  
Keyword(s):  
Experimental Data ◽  
Biological Networks ◽  
Topological Analysis ◽  
Data Sets ◽  
Network Nodes ◽  
Biological Network Analysis ◽  
Lab Experiments ◽  
New Perspective ◽  
Centrality Analysis ◽  
Important Nodes

The growing dimension and complexity of available experimental data generating biological networks has increased the need for tools allowing to categorize nodes by their topological relevance in biological networks. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes for the identification of the most important nodes of a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be also integrated with data sets from lab experiments, such as expression or phosphorylation levels of the proteins represented in the network, using the graphical features of the tool. This opens a new perspective in the analysis of biological networks, since integration of topological analysis with lab experimental data can increase the predictive power of a bioinformatical analysis.

scholarly journals Reproducing scientists’ mobility: a data-driven model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giacomo Vaccario ◽  
Luca Verginer ◽  
Frank Schweitzer
Keyword(s):  
Decision Rules ◽  
Migration Policy ◽  
Large Data ◽  
Global Scale ◽  
Global Network ◽  
Data Sets ◽  
Mobility Patterns ◽  
Agent Based ◽  
Hiring Process ◽  
Geographical Distances

AbstractHigh skill labour is an important factor underpinning the competitive advantage of modern economies. Therefore, attracting and retaining scientists has become a major concern for migration policy. In this work, we study the migration of scientists on a global scale, by combining two large data sets covering the publications of 3.5 million scientists over 60 years. We analyse their geographical distances moved for a new affiliation and their age when moving, this way reconstructing their geographical “career paths”. These paths are used to derive the world network of scientists’ mobility between cities and to analyse its topological properties. We further develop and calibrate an agent-based model, such that it reproduces the empirical findings both at the level of scientists and of the global network. Our model takes into account that the academic hiring process is largely demand-driven and demonstrates that the probability of scientists to relocate decreases both with age and with distance. Our results allow interpreting the model assumptions as micro-based decision rules that can explain the observed mobility patterns of scientists.

Constrained Petri Nets. Part II: Generalizations and extensions

1983 ◽  
Vol 6 (3-4) ◽  
pp. 333-374
Author(s):  
H.J.M. Goeman ◽  
L.P.J. Groenewegen ◽  
H.C.M. Kleijn ◽  
G. Rozenberg
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Theoretical Framework ◽  
General Constraints ◽  
Context Free ◽  
Boolean Expressions

This paper continues the investigation froll1 [Goeman et al.] concerning the use of sets of places of a Petri net as additional (to input places) constraints for granting concession. Now interpretations of more general constraints are considered and expressed as Boolean expressions. This gives rise to various classes of constrained Petri nets. These are compared in the language theoretical framework introduced in [Goeman et al.]. An upperbound for the language defining power is found in the class of context-free programmed languages.

An Axiomatic Characterization of a Class of Petri Nets

1991 ◽  
Vol 14 (4) ◽  
pp. 477-491
Author(s):  
Waldemar Korczynski
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Axiomatic Characterization ◽  
Algebraic Characterization

In this paper an algebraic characterization of a class of Petri nets is given. The nets are characterized by a kind of algebras, which can be considered as a generalization of the concept of the case graph of a (marked) Petri net.

The Quantitative Assessment of Domino Effects Based on Stochastic Petri Nets

2008 ◽  
Vol 44-46 ◽  
pp. 537-544
Author(s):  
Shi Yi Bao ◽  
Jian Xin Zhu ◽  
Li J. Wang ◽  
Ning Jiang ◽  
Zeng Liang Gao
Keyword(s):  
Petri Nets ◽  
State Space ◽  
Petri Net ◽  
Quantitative Assessment ◽  
Stochastic Petri Nets ◽  
Industrial Park ◽  
Domino Effect ◽  
State Space Explosion ◽  
Stochastic Petri Net ◽  
Chemical Industrial Park

The quantitative analysis of “domino” effects is one of the main aspects of hazard assessment in chemical industrial park. This paper demonstrates the application of heterogeneous stochastic Petri net modeling techniques to the quantitative assessment of the probabilities of domino effects of major accidents in chemical industrial park. First, five events are included in the domino effect models of major accidents: pool fire, explosion, boiling liquid expanding vapour explosion (BLEVE) giving rise to a fragment, jet fire and delayed explosion of a vapour cloud. Then, the domino effect models are converted into Generalized Stochastic Petri net (GSPN) in which the probability of the domino effect is calculated automatically. The Stochastic Petri nets’ models, which are state-space based ones, increase the modeling flexibility but create the state-space explosion problems. Finally, in order to alleviate the state-space explosion problems of GSPN models, this paper employs Stochastic Wellformed Net (SWN), a particular class of High-Level (colored) SPN. To conduct a case study on a chemical industrial park, the probability of domino effects of major accidents is calculated by using the GSPN model and SWN model in this paper.

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