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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...

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Detalles Bibliográficos
Autores principales: Zeng, Heyuan, Zhang, Jinbiao, Preising, Gabriel A, Rubel, Tobias, Singh, Pramesh, Ritz, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
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/.
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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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