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SNAVI: Desktop application for analysis and visualization of large-scale signaling networks
BACKGROUND: Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as lin...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2637233/ https://www.ncbi.nlm.nih.gov/pubmed/19154595 http://dx.doi.org/10.1186/1752-0509-3-10 |
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author | Ma'ayan, Avi Jenkins, Sherry L Webb, Ryan L Berger, Seth I Purushothaman, Sudarshan P Abul-Husn, Noura S Posner, Jeremy M Flores, Tony Iyengar, Ravi |
author_facet | Ma'ayan, Avi Jenkins, Sherry L Webb, Ryan L Berger, Seth I Purushothaman, Sudarshan P Abul-Husn, Noura S Posner, Jeremy M Flores, Tony Iyengar, Ravi |
author_sort | Ma'ayan, Avi |
collection | PubMed |
description | BACKGROUND: Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge. RESULTS: SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names. CONCLUSION: SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: . The source code can be accessed from: |
format | Text |
id | pubmed-2637233 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-26372332009-02-07 SNAVI: Desktop application for analysis and visualization of large-scale signaling networks Ma'ayan, Avi Jenkins, Sherry L Webb, Ryan L Berger, Seth I Purushothaman, Sudarshan P Abul-Husn, Noura S Posner, Jeremy M Flores, Tony Iyengar, Ravi BMC Syst Biol Software BACKGROUND: Studies of cellular signaling indicate that signal transduction pathways combine to form large networks of interactions. Viewing protein-protein and ligand-protein interactions as graphs (networks), where biomolecules are represented as nodes and their interactions are represented as links, is a promising approach for integrating experimental results from different sources to achieve a systematic understanding of the molecular mechanisms driving cell phenotype. The emergence of large-scale signaling networks provides an opportunity for topological statistical analysis while visualization of such networks represents a challenge. RESULTS: SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names. CONCLUSION: SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software. The installation may be downloaded from: . The source code can be accessed from: BioMed Central 2009-01-20 /pmc/articles/PMC2637233/ /pubmed/19154595 http://dx.doi.org/10.1186/1752-0509-3-10 Text en Copyright © 2009 Ma'ayan et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Ma'ayan, Avi Jenkins, Sherry L Webb, Ryan L Berger, Seth I Purushothaman, Sudarshan P Abul-Husn, Noura S Posner, Jeremy M Flores, Tony Iyengar, Ravi SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title | SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title_full | SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title_fullStr | SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title_full_unstemmed | SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title_short | SNAVI: Desktop application for analysis and visualization of large-scale signaling networks |
title_sort | snavi: desktop application for analysis and visualization of large-scale signaling networks |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2637233/ https://www.ncbi.nlm.nih.gov/pubmed/19154595 http://dx.doi.org/10.1186/1752-0509-3-10 |
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