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Graphery: interactive tutorials for biological network algorithms
Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts freque...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262715/ https://www.ncbi.nlm.nih.gov/pubmed/34037782 http://dx.doi.org/10.1093/nar/gkab420 |
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author | Zeng, Heyuan Zhang, Jinbiao Preising, Gabriel A Rubel, Tobias Singh, Pramesh Ritz, Anna |
author_facet | Zeng, Heyuan Zhang, Jinbiao Preising, Gabriel A Rubel, Tobias Singh, Pramesh Ritz, Anna |
author_sort | Zeng, Heyuan |
collection | PubMed |
description | Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/. |
format | Online Article Text |
id | pubmed-8262715 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82627152021-07-08 Graphery: interactive tutorials for biological network algorithms Zeng, Heyuan Zhang, Jinbiao Preising, Gabriel A Rubel, Tobias Singh, Pramesh Ritz, Anna Nucleic Acids Res Web Server Issue Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/. Oxford University Press 2021-05-25 /pmc/articles/PMC8262715/ /pubmed/34037782 http://dx.doi.org/10.1093/nar/gkab420 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Zeng, Heyuan Zhang, Jinbiao Preising, Gabriel A Rubel, Tobias Singh, Pramesh Ritz, Anna Graphery: interactive tutorials for biological network algorithms |
title |
Graphery: interactive tutorials for biological network algorithms |
title_full |
Graphery: interactive tutorials for biological network algorithms |
title_fullStr |
Graphery: interactive tutorials for biological network algorithms |
title_full_unstemmed |
Graphery: interactive tutorials for biological network algorithms |
title_short |
Graphery: interactive tutorials for biological network algorithms |
title_sort | graphery: interactive tutorials for biological network algorithms |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262715/ https://www.ncbi.nlm.nih.gov/pubmed/34037782 http://dx.doi.org/10.1093/nar/gkab420 |
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