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Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters
Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korea Genome Organization
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808643/ https://www.ncbi.nlm.nih.gov/pubmed/31610621 http://dx.doi.org/10.5808/GI.2019.17.3.e25 |
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author | Kim, Ji-Hyeon Nam, Hee-Jo Park, Hyun-Seok |
author_facet | Kim, Ji-Hyeon Nam, Hee-Jo Park, Hyun-Seok |
author_sort | Kim, Ji-Hyeon |
collection | PubMed |
description | Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating to article categories, word clouds, and the most-studied genes, drawing on recent reviews of the use of word frequencies in journal articles. Trends in the studies published in Genomics & Informatics are discussed both individually and collectively. |
format | Online Article Text |
id | pubmed-6808643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korea Genome Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-68086432019-10-24 Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters Kim, Ji-Hyeon Nam, Hee-Jo Park, Hyun-Seok Genomics Inform Mini Review Genomics & Informatics (NLM title abbreviation: Genomics Inform) is the official journal of the Korea Genome Organization. Herein, we conduct a statistical analysis of the publications of Genomics & Informatics over the 16 years since its inception, with a particular focus on issues relating to article categories, word clouds, and the most-studied genes, drawing on recent reviews of the use of word frequencies in journal articles. Trends in the studies published in Genomics & Informatics are discussed both individually and collectively. Korea Genome Organization 2019-09-27 /pmc/articles/PMC6808643/ /pubmed/31610621 http://dx.doi.org/10.5808/GI.2019.17.3.e25 Text en (c) 2019, Korea Genome Organization (CC) 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 is properly cited. |
spellingShingle | Mini Review Kim, Ji-Hyeon Nam, Hee-Jo Park, Hyun-Seok Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title | Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title_full | Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title_fullStr | Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title_full_unstemmed | Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title_short | Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
title_sort | trends in genomics & informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
topic | Mini Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808643/ https://www.ncbi.nlm.nih.gov/pubmed/31610621 http://dx.doi.org/10.5808/GI.2019.17.3.e25 |
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