Trends in : 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...
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| Format: | Article |
| Language: | English |
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BioMed Central
2019-09-01
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| Series: | Genomics & Informatics |
| Subjects: | |
| Online Access: | http://genominfo.org/upload/pdf/gi-2019-17-3-e25.pdf |
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| _version_ | 1832569893840486400 |
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| author | Ji-Hyeon Kim Hee-Jo Nam Hyun-Seok Park |
| author_facet | Ji-Hyeon Kim Hee-Jo Nam Hyun-Seok Park |
| author_sort | Ji-Hyeon Kim |
| collection | DOAJ |
| 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 | Article |
| id | doaj-art-c3657a0ca15549548e1f50b409e24775 |
| institution | Kabale University |
| issn | 2234-0742 |
| language | English |
| publishDate | 2019-09-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-c3657a0ca15549548e1f50b409e247752025-02-02T19:04:10ZengBioMed CentralGenomics & Informatics2234-07422019-09-0117310.5808/GI.2019.17.3.e25575Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clustersJi-Hyeon Kim0Hee-Jo Nam1Hyun-Seok Park2 Bioinformatics Laboratory, ELTEC College of Engineering, Ewha Womans University, Seoul 03760, Korea Bioinformatics Laboratory, ELTEC College of Engineering, Ewha Womans University, Seoul 03760, Korea Bioinformatics Laboratory, ELTEC College of Engineering, Ewha Womans University, Seoul 03760, KoreaGenomics & 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.http://genominfo.org/upload/pdf/gi-2019-17-3-e25.pdfdocument clusteringgenesshallow neural networkword cloud |
| spellingShingle | Ji-Hyeon Kim Hee-Jo Nam Hyun-Seok Park Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters Genomics & Informatics document clustering genes shallow neural network word cloud |
| title | Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
| title_full | Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
| title_fullStr | Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
| title_full_unstemmed | Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
| title_short | Trends in : a statistical review of publications from 2003 to 2018 focusing on the most-studied genes and document clusters |
| title_sort | trends in a statistical review of publications from 2003 to 2018 focusing on the most studied genes and document clusters |
| topic | document clustering genes shallow neural network word cloud |
| url | http://genominfo.org/upload/pdf/gi-2019-17-3-e25.pdf |
| work_keys_str_mv | AT jihyeonkim trendsinastatisticalreviewofpublicationsfrom2003to2018focusingonthemoststudiedgenesanddocumentclusters AT heejonam trendsinastatisticalreviewofpublicationsfrom2003to2018focusingonthemoststudiedgenesanddocumentclusters AT hyunseokpark trendsinastatisticalreviewofpublicationsfrom2003to2018focusingonthemoststudiedgenesanddocumentclusters |