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Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks

The reasons for selecting a gene for further study might vary from historical momentum to funding availability, thus leading to unequal attention distribution among all genes. However, certain biological features tend to be overlooked in evaluating a gene’s popularity. Here we present a meta-analysi...

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Autores principales: Mihai, Ionut Sebastian, Das, Debojyoti, Maršalkaite, Gabija, Henriksson, Johan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926953/
https://www.ncbi.nlm.nih.gov/pubmed/33672419
http://dx.doi.org/10.3390/genes12020319
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author Mihai, Ionut Sebastian
Das, Debojyoti
Maršalkaite, Gabija
Henriksson, Johan
author_facet Mihai, Ionut Sebastian
Das, Debojyoti
Maršalkaite, Gabija
Henriksson, Johan
author_sort Mihai, Ionut Sebastian
collection PubMed
description The reasons for selecting a gene for further study might vary from historical momentum to funding availability, thus leading to unequal attention distribution among all genes. However, certain biological features tend to be overlooked in evaluating a gene’s popularity. Here we present a meta-analysis of the reasons why different genes have been studied and to what extent, with a focus on the gene-specific biological features. From unbiased datasets we can define biological properties of genes that reasonably may affect their perceived importance. We make use of both linear and nonlinear computational approaches for estimating gene popularity to then compare their relative importance. We find that roughly 25% of the studies are the result of a historical positive feedback, which we may think of as social reinforcement. Of the remaining features, gene family membership is the most indicative followed by disease relevance and finally regulatory pathway association. Disease relevance has been an important driver until the 1990s, after which the focus shifted to exploring every single gene. We also present a resource that allows one to study the impact of reinforcement, which may guide our research toward genes that have not yet received proportional attention.
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spelling pubmed-79269532021-03-04 Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks Mihai, Ionut Sebastian Das, Debojyoti Maršalkaite, Gabija Henriksson, Johan Genes (Basel) Article The reasons for selecting a gene for further study might vary from historical momentum to funding availability, thus leading to unequal attention distribution among all genes. However, certain biological features tend to be overlooked in evaluating a gene’s popularity. Here we present a meta-analysis of the reasons why different genes have been studied and to what extent, with a focus on the gene-specific biological features. From unbiased datasets we can define biological properties of genes that reasonably may affect their perceived importance. We make use of both linear and nonlinear computational approaches for estimating gene popularity to then compare their relative importance. We find that roughly 25% of the studies are the result of a historical positive feedback, which we may think of as social reinforcement. Of the remaining features, gene family membership is the most indicative followed by disease relevance and finally regulatory pathway association. Disease relevance has been an important driver until the 1990s, after which the focus shifted to exploring every single gene. We also present a resource that allows one to study the impact of reinforcement, which may guide our research toward genes that have not yet received proportional attention. MDPI 2021-02-23 /pmc/articles/PMC7926953/ /pubmed/33672419 http://dx.doi.org/10.3390/genes12020319 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mihai, Ionut Sebastian
Das, Debojyoti
Maršalkaite, Gabija
Henriksson, Johan
Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title_full Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title_fullStr Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title_full_unstemmed Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title_short Meta-Analysis of Gene Popularity: Less Than Half of Gene Citations Stem from Gene Regulatory Networks
title_sort meta-analysis of gene popularity: less than half of gene citations stem from gene regulatory networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926953/
https://www.ncbi.nlm.nih.gov/pubmed/33672419
http://dx.doi.org/10.3390/genes12020319
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