Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003– 2018

Ji Hye Oh; Hee Jo Nam; Hyun Seok Park

doi:10.5808/gi.21074

Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003– 2018

Ji Hye Oh, Hee Jo Nam, Hyun Seok Park

Department of Computer Science & Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bio-informatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were re-viewed. Content analysis was the main method employed in the current research. The re-sults were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

Original language	English
Article number	e51
Journal	Genomics and Informatics
Volume	19
Issue number	4
DOIs	https://doi.org/10.5808/gi.21074
State	Published - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021, Korea Genome Organization. All rights reserved.

Keywords

Content analysis
Document clustering
Neural network
Word embedding

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.5808/gi.21074

Cite this

@article{5e063f83cadc4370a84166cf203898da,

title = "Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003– 2018",

abstract = "This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bio-informatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were re-viewed. Content analysis was the main method employed in the current research. The re-sults were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).",

keywords = "Content analysis, Document clustering, Neural network, Word embedding",

author = "Oh, {Ji Hye} and Nam, {Hee Jo} and Park, {Hyun Seok}",

year = "2021",

month = dec,

doi = "10.5808/gi.21074",

language = "English",

volume = "19",

journal = "Genomics and Informatics",

issn = "2234-0742",

publisher = "Korea Genome Organization",

number = "4",

}

TY - JOUR

T1 - Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003– 2018

AU - Oh, Ji Hye

AU - Nam, Hee Jo

AU - Park, Hyun Seok

PY - 2021/12

Y1 - 2021/12

N2 - This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bio-informatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were re-viewed. Content analysis was the main method employed in the current research. The re-sults were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

AB - This study explored the trends of Genomics & Informatics during the period of 2003-2018 in comparison with 11 other scholarly journals: BMC Bioinformatics, Algorithms for Molecular Biology: AMB, BMC Systems Biology, Journal of Computational Biology, Briefings in Bio-informatics, BMC Genomics, Nucleic Acids Research, American Journal of Human Genetics, Oncogenesis, Disease Markers, and Microarrays. In total, 22,423 research articles were re-viewed. Content analysis was the main method employed in the current research. The re-sults were interpreted using descriptive analysis, a clustering analysis, word embedding, and deep learning techniques. Trends are discussed for the 12 journals, both individually and collectively. This is an extension of our previous study (PMCID: PMC6808643).

KW - Content analysis

KW - Document clustering

KW - Neural network

KW - Word embedding

UR - http://www.scopus.com/inward/record.url?scp=85126883910&partnerID=8YFLogxK

U2 - 10.5808/gi.21074

DO - 10.5808/gi.21074

M3 - Article

AN - SCOPUS:85126883910

SN - 2234-0742

VL - 19

JO - Genomics and Informatics

JF - Genomics and Informatics

IS - 4

M1 - e51

ER -

Estimation of the journal distance of Genomics & Informatics from other bioinformatics-driven journals, 2003– 2018

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this