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MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers

BACKGROUND: The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge...

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Autores principales: Allot, Alexis, Chennen, Kirsley, Nevers, Yannis, Poidevin, Laetitia, Kress, Arnaud, Ripp, Raymond, Thompson, Julie Dawn, Poch, Olivier, Lecompte, Odile
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493784/
https://www.ncbi.nlm.nih.gov/pubmed/28623182
http://dx.doi.org/10.2196/jmir.6676
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author Allot, Alexis
Chennen, Kirsley
Nevers, Yannis
Poidevin, Laetitia
Kress, Arnaud
Ripp, Raymond
Thompson, Julie Dawn
Poch, Olivier
Lecompte, Odile
author_facet Allot, Alexis
Chennen, Kirsley
Nevers, Yannis
Poidevin, Laetitia
Kress, Arnaud
Ripp, Raymond
Thompson, Julie Dawn
Poch, Olivier
Lecompte, Odile
author_sort Allot, Alexis
collection PubMed
description BACKGROUND: The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. OBJECTIVE: MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. METHODS: MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. RESULTS: MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. CONCLUSIONS: We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends.
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spelling pubmed-54937842017-07-11 MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers Allot, Alexis Chennen, Kirsley Nevers, Yannis Poidevin, Laetitia Kress, Arnaud Ripp, Raymond Thompson, Julie Dawn Poch, Olivier Lecompte, Odile J Med Internet Res Original Paper BACKGROUND: The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. OBJECTIVE: MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. METHODS: MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. RESULTS: MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user’s specific interests and provides an efficient way to share information with collaborators. Furthermore, the user’s behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. CONCLUSIONS: We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. JMIR Publications 2017-06-16 /pmc/articles/PMC5493784/ /pubmed/28623182 http://dx.doi.org/10.2196/jmir.6676 Text en ©Alexis Allot, Kirsley Chennen, Yannis Nevers, Laetitia Poidevin, Arnaud Kress, Raymond Ripp, Julie Dawn Thompson, Olivier Poch, Odile Lecompte. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.06.2017. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Allot, Alexis
Chennen, Kirsley
Nevers, Yannis
Poidevin, Laetitia
Kress, Arnaud
Ripp, Raymond
Thompson, Julie Dawn
Poch, Olivier
Lecompte, Odile
MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title_full MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title_fullStr MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title_full_unstemmed MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title_short MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers
title_sort mygenefriends: a social network linking genes, genetic diseases, and researchers
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493784/
https://www.ncbi.nlm.nih.gov/pubmed/28623182
http://dx.doi.org/10.2196/jmir.6676
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