Trends in Genomics & Informatics: a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters
- Author:
Ji Hyeon KIM
1
;
Hee Jo NAM
;
Hyun Seok PARK
Author Information
- Publication Type:Review
- Keywords: document clustering; genes; shallow neural network; word cloud
- MeSH: Genome; Genomics; Informatics; Korea
- From:Genomics & Informatics 2019;17(3):e25-
- CountryRepublic of Korea
- Language:English
- Abstract: 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.
