Development of an integrated network visualisation and graph analysis tool for biological networks

2012 ◽  
Vol 5 (2) ◽  
pp. 152
Author(s):  
Ying Tang ◽  
David Carbonetta ◽  
Sachin Shetty
Keyword(s):  
Biological Networks ◽  
Graph Analysis ◽  
Analysis Tool ◽  
Integrated Network

scholarly journals Network architectures supporting learnability

2020 ◽  
Vol 375 (1796) ◽  
pp. 20190323 ◽  
Author(s):  
Perry Zurn ◽  
Danielle S. Bassett
Keyword(s):  
Biological Networks ◽  
Statistical Physics ◽  
Knowledge Network ◽  
Network Architectures ◽  
Philosophical Discussion ◽  
Hierarchical Networks ◽  
Integrated Network ◽  
Physical Constraints ◽  
Philosophical Foundations ◽  
Relational Knowledge

Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit—the brain—that encodes and processes the information. That is, learning is reliant on integrated network architectures at two levels: the epistemic and the computational, or the conceptual and the neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that instantiate the principles of thermodynamics and information theory to offer an explanatory model for such constraints. We then highlight similarities between those constraints on the learnability of relational networks, at one level, and the physical constraints on the development of interconnected patterns in neural systems, at another level, both leading to hierarchically modular networks. To support our discussion of these similarities, we employ an operational distinction between the modeller (e.g. the human brain), the model (e.g. a single human’s knowledge) and the modelled (e.g. the information present in our experiences). We then turn to a philosophical discussion of whether and how we can extend our observations to a claim regarding explanation and mechanism for knowledge acquisition. What relation between hierarchical networks, at the conceptual and neural levels, best facilitate learning? Are the architectures of optimally learnable networks a topological reflection of the architectures of comparably developed neural networks? Finally, we contribute to a unified approach to hierarchies and levels in biological networks by proposing several epistemological norms for analysing the computational brain and social epistemes, and for developing pedagogical principles conducive to curious thought. This article is part of the theme issue ‘Unifying the essential concepts of biological networks: biological insights and philosophical foundations’.

TAG: Topological Attack Graph Analysis Tool

2019 ◽  
Author(s):  
Marek Malowidzki ◽  
Damian Hermanowski ◽  
Przemyslaw Berezinski
Keyword(s):  
Graph Analysis ◽  
Analysis Tool ◽  
Attack Graph

Thermodynamic-based computational profiling of cellular regulatory control in hepatocyte metabolism

2005 ◽  
Vol 288 (3) ◽  
pp. E633-E644 ◽  
Author(s):  
Daniel A. Beard ◽  
Hong Qian
Keyword(s):  
Biological Networks ◽  
Drug Targets ◽  
Metabolic Diseases ◽  
Cell Metabolism ◽  
Glucose Production ◽  
Glycogen Metabolism ◽  
Metabolic Model ◽  
Regulatory Control ◽  
Integrated Network ◽  
Network Function

Thermodynamic-based constraints on biochemical fluxes and concentrations are applied in concert with mass balance of fluxes in glycogenesis and glycogenolysis in a model of hepatic cell metabolism. Constraint-based modeling methods that facilitate predictions of reactant concentrations, reaction potentials, and enzyme activities are introduced to identify putative regulatory and control sites in biological networks by computing the minimal control scheme necessary to switch between metabolic modes. Computational predictions of control sites in glycogenic and glycogenolytic operational modes in the hepatocyte network compare favorably with known regulatory mechanisms. The developed hepatic metabolic model is used to computationally analyze the impairment of glucose production in von Gierke's and Hers' diseases, two metabolic diseases impacting glycogen metabolism. The computational methodology introduced here can be generalized to identify downstream targets of agonists, to systematically probe possible drug targets, and to predict the effects of specific inhibitors (or activators) on integrated network function.

Formal integrated network security analysis tool: formal query‐based network security configuration analysis

IET Networks ◽  
2015 ◽  
Vol 4 (2) ◽  
pp. 137-147 ◽  
Author(s):  
Soumya Maity ◽  
P. Bera ◽  
Soumya K. Ghosh ◽  
Ehab Al‐Shaer
Keyword(s):  
Network Security ◽  
Security Analysis ◽  
Analysis Tool ◽  
Integrated Network ◽  
Security Configuration

An empirical test of the accuracy of an attack graph analysis tool

2015 ◽  
Vol 23 (5) ◽  
pp. 516-531 ◽  
Author(s):  
Teodor Sommestad ◽  
Fredrik Sandström
Keyword(s):  
Empirical Test ◽  
Graph Analysis ◽  
Analysis Tool ◽  
Attack Graph

scholarly journals Conceptualizing “Family” and the Role of “Chosen Family” within the LGBTQ+ Refugee Community: A Text Network Graph Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 369
Author(s):  
Seohyun Kim ◽  
Israel Fisseha Feyissa
Keyword(s):  
Family Relationships ◽  
Research Community ◽  
Graph Analysis ◽  
Analysis Tool ◽  
Network Graph ◽  
Relevant Research ◽  
Refugee Community ◽  
Biological Family ◽  
Youtube Videos

This study analyzed meaning attributions regarding “family” and “chosen family” by Lesbian, Gay, Bisexual, Pansexual, Transgender, Gender Queer, Queer, Intersex, Agender, Asexual, and other Queer-identifying community (LGBTQ+) refugees. The meaning and significance of a chosen family in the newly established life of the refugees was also pin-pointed for its value of safekeeping the wellbeing and settlement process. We analyzed narrative statements given by 67 LGBTQ+ refugees from 82 YouTube videos. Using InfraNodus, a text graph analysis tool, we identified pathways for meaning circulation within the narrative data, and generated a contextualized meaning for family and chosen family. The conceptualization process produced a deduction within family relationships, exploring why people, other than in biological relationships, appear to be vital in their overall wellbeing and settlement, as well as the process through which this occurs. Biological family is sometimes associated with words that instigate fear, danger, and insecurity, while the concept of chosen family is associated with words like trusting, like-minded, understanding, welcoming, loving, committed, etc. The results of the study are intended to add knowledge to the gap by showing the types and characteristics of family relationships in LGBTQ+ refugee settings. It is also a call for the relevant research community to produce more evidence in such settings, as this is essential for obtaining a better understanding of these issues.

scholarly journals Biological Network Analysis of Genes Involve in Embryogenesis of Oil Palm using ClueGO

2017 ◽  
Vol 3 (4) ◽  
pp. 265
Author(s):  
Widyartini Made Sudania ◽  
Zulfikar Achmad Tanjung ◽  
Nurita Toruan-Mathius ◽  
Tony Liwang
Keyword(s):  
Dna Sequencing ◽  
Oil Palm ◽  
Biological Networks ◽  
Expressed Sequence Tag ◽  
Large Data ◽  
Data Interpretation ◽  
Analysis Tool ◽  
Sequencing Data ◽  
Data Set ◽  
Kegg Pathways

<p class="Els-Abstract-text">The application of DNA sequencing technologies has a major impact on molecular biology, especially in understanding genes interaction in a certain condition. Due to a large number of genes produced by this high-throughput technology, a proper analysis tool is needed for data interpretation. ClueGO is a bioinformatics tool, an easy to use Cytoscape plug-in that strongly improves biological function interpretation of genes. It analyzes a cluster or comparing two clusters and comprehensively visualizes their group functions. This tool is applied to identify biological networks of genes involved in embryogenesis of oil palm, the most critical phase in oil palm tissue culture process. Two ESTs sequencing data from the GenBank database under accession number EY396120-EY413718 and DW247764-DW248770 were used in this study. Fifty-two and one hundred eight groups of genes were identified using biological process in Gene Ontology setting from the database of EY396120-EY413718 and DW247764-DW248770, respectively. Thirty-one groups of genes were consistently occurred in both ESTs. According to the literature, these genes play an important role in cell formations and developments, stresses and stimulus responses, photosynthesis and metabolic processes that indicate the involvement of these groups of genes in oil palm embryogenesis processes. ClueGO is the appropriate tool to analyze a large data set of genes in a specific condition, such as embryogenesis of oil palm.</p><div><p class="Els-keywords"><em> </em></p></div><strong>Keywords:</strong> callus embryogenesis; Cytoscape plug-in; DNA sequencing; expressed sequence tag; KEGG pathways

Topological Analysis of Axon Guidance Network for Homo Sapiens

2011 ◽  
pp. 93-102
Author(s):  
Xuning Chen ◽  
Weiping Zhu
Keyword(s):  
Neural Networks ◽  
Network Analysis ◽  
Axon Guidance ◽  
Biological Networks ◽  
Visual Analysis ◽  
Homo Sapiens ◽  
Topological Analysis ◽  
Signal Molecules ◽  
Analysis Tool ◽  
Topological Properties

Axonal outgrowth is usually guided by a variety of guidance factors, such as netrins, ephrins, slits and semaphorins, and is one of the critical steps for the proper formation of neural networks. However, how the signal molecules function and why some of these play more important roles than others in guiding the axonal directional outgrowth has not been fully understood. In this study, we try to solve the problem by using the complex network analysis method. The signal molecules and interactions are treated as the nodes and edges to construct the axon guidance network model for Homo sapiens. The data of the model are taken from the KEGG database, and an analysis workbench named Integrative Visual Analysis Tool for Biological Networks and Pathways (VisANT) is employed to analyze the topological properties, including the degree distribution and the top co-expressed genes of the axon guidance network. This study has just opened a window into understanding the mechanism of axon guidance.

NetSets.js: a JavaScript framework for compositional assessment and comparison of biological networks through Venn-integrated network diagrams

2020 ◽  
Author(s):  
Sunil Nagpal ◽  
Bhusan K Kuntal ◽  
Sharmila S Mande
Keyword(s):  
Protein Interactions ◽  
Biological Networks ◽  
Web Application ◽  
Gene Interaction ◽  
Supplementary Information ◽  
Venn Diagram ◽  
Protein Protein Interactions ◽  
Integrated Network ◽  
Network Diagram ◽  
Network Diagrams

Abstract Motivation Venn diagrams are frequently used to compare composition of datasets (e.g. datasets containing list of proteins and genes). Network diagram constructed using such datasets are usually generated using ‘list of edges’, popularly known as edge-lists. An edge-list and the corresponding generated network are, however, composed of two elements, namely, edges (e.g. protein–protein interactions) and nodes (e.g. proteins). Researchers often use individual lists of edges and nodes to compare composition of biological networks using existing Venn diagram tools. However, specialized analysis workflows are required for comparison of nodes as well as edges. Apart from this, different tools or graph libraries are needed for visualizing any specific edges of interest (e.g. protein–protein interactions which are present across all networks or are shared between subset of networks or are exclusively present in a selected network). Further, these results are required to be exported in the form of publication worthy network diagram(s), particularly for small networks. Results We introduce a (server independent) JavaScript framework (called NetSets.js) that integrates popular Venn and network diagrams in a single application. A free to use intuitive web application (utilizing NetSets.js), specifically designed to perform both compositional comparisons (e.g. for identifying common/exclusive edges or nodes) and interactive user defined visualizations of network (for the identified common/exclusive interactions across multiple networks) using simple edge-lists is also presented. The tool also enables connection to Cytoscape desktop application using the Netsets-Cyapp. We demonstrate the utility of our tool using real world biological networks (microbiome, gene interaction, multiplex and protein–protein interaction networks). Availabilityand implementation http://web.rniapps.net/netsets (freely available for academic use). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Integrated querying and version control of context-specific biological networks

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Tyler Cowman ◽  
Mustafa Coşkun ◽  
Ananth Grama ◽  
Mehmet Koyutürk
Keyword(s):  
Data Structures ◽  
Biological Networks ◽  
Computational Cost ◽  
Tissue Type ◽  
Large Network ◽  
Integrated Network ◽  
Compressed Data Structures ◽  
Tree Data ◽  
Context Specific ◽  
Tree Data Structure

Abstract Motivation Biomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often specializations of generic interaction sets, presenting opportunities for reducing storage and computational cost. Therefore, it is desirable to develop effective compression and storage techniques, along with efficient algorithms and a flexible query interface capable of operating on compressed data structures. Current graph databases offer varying levels of support for network integration. However, these solutions do not provide efficient methods for the storage and querying of versioned networks. Results We present VerTIoN, a framework consisting of novel data structures and associated query mechanisms for integrated querying of versioned context-specific biological networks. As a use case for our framework, we study network proximity queries in which the user can select and compose a combination of tissue-specific and generic networks. Using our compressed version tree data structure, in conjunction with state-of-the-art numerical techniques, we demonstrate real-time querying of large network databases. Conclusion Our results show that it is possible to support flexible queries defined on heterogeneous networks composed at query time while drastically reducing response time for multiple simultaneous queries. The flexibility offered by VerTIoN in composing integrated network versions opens significant new avenues for the utilization of ever increasing volume of context-specific network data in a broad range of biomedical applications. Availability and Implementation VerTIoN is implemented as a C++ library and is available at http://compbio.case.edu/omics/software/vertion and https://github.com/tjcowman/vertion Contact [email protected]

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