Mapping miRNA research in schizophrenia: a scientometric review

Micro RNA (miRNA) research has great implications in uncovering the aetiology of neuropsychiatric conditions due to the role of miRNA in brain development and function. Schizophrenia, a complex yet devastating neuropsychiatric disorder, is one such condition that had been extensively studied in the...

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Main Authors: Lim, Mengyu, Carollo, Alessandro, Neoh, Michelle Jin Yee, Esposito, Gianluca
Other Authors: School of Social Sciences
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/169557
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1695572023-07-30T15:30:30Z Mapping miRNA research in schizophrenia: a scientometric review Lim, Mengyu Carollo, Alessandro Neoh, Michelle Jin Yee Esposito, Gianluca School of Social Sciences Social sciences::Psychology miRNA Schizophrenia Micro RNA (miRNA) research has great implications in uncovering the aetiology of neuropsychiatric conditions due to the role of miRNA in brain development and function. Schizophrenia, a complex yet devastating neuropsychiatric disorder, is one such condition that had been extensively studied in the realm of miRNA. Although a relatively new field of research, this area of study has progressed sufficiently to warrant dozens of reviews summarising findings from past to present. However, as a majority of reviews cannot encapsulate the full body of research, there is still a need to synthesise the diversity of publications made in this area in a systematic but easy-to-understand manner. Therefore, this study adopted bibliometrics and scientometrics, specifically document co-citation analysis (DCA), to review the literature on miRNAs in the context of schizophrenia over the course of history. From a literature search on Scopus, 992 papers were found and analysed with CiteSpace. DCA analysis generated a network of 13 major clusters with different thematic focuses within the subject area. Finally, these clusters are qualitatively discussed. miRNA research has branched into schizophrenia, among other medical and psychiatric conditions, due to previous findings in other forms of non-coding RNA. With the rise of big data, bioinformatics analyses are increasingly common in this field of research. The future of research is projected to rely more heavily on interdisciplinary collaboration. Additionally, it can be expected that there will be more translational studies focusing on the application of these findings to the development of effective treatments. Published version 2023-07-24T06:38:39Z 2023-07-24T06:38:39Z 2023 Journal Article Lim, M., Carollo, A., Neoh, M. J. Y. & Esposito, G. (2023). Mapping miRNA research in schizophrenia: a scientometric review. International Journal of Molecular Sciences, 24(1), 436-. https://dx.doi.org/10.3390/ijms24010436 1661-6596 https://hdl.handle.net/10356/169557 10.3390/ijms24010436 36613876 2-s2.0-85145934098 1 24 436 en International Journal of Molecular Sciences © 2022 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 (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Social sciences::Psychology
miRNA
Schizophrenia
spellingShingle Social sciences::Psychology
miRNA
Schizophrenia
Lim, Mengyu
Carollo, Alessandro
Neoh, Michelle Jin Yee
Esposito, Gianluca
Mapping miRNA research in schizophrenia: a scientometric review
description Micro RNA (miRNA) research has great implications in uncovering the aetiology of neuropsychiatric conditions due to the role of miRNA in brain development and function. Schizophrenia, a complex yet devastating neuropsychiatric disorder, is one such condition that had been extensively studied in the realm of miRNA. Although a relatively new field of research, this area of study has progressed sufficiently to warrant dozens of reviews summarising findings from past to present. However, as a majority of reviews cannot encapsulate the full body of research, there is still a need to synthesise the diversity of publications made in this area in a systematic but easy-to-understand manner. Therefore, this study adopted bibliometrics and scientometrics, specifically document co-citation analysis (DCA), to review the literature on miRNAs in the context of schizophrenia over the course of history. From a literature search on Scopus, 992 papers were found and analysed with CiteSpace. DCA analysis generated a network of 13 major clusters with different thematic focuses within the subject area. Finally, these clusters are qualitatively discussed. miRNA research has branched into schizophrenia, among other medical and psychiatric conditions, due to previous findings in other forms of non-coding RNA. With the rise of big data, bioinformatics analyses are increasingly common in this field of research. The future of research is projected to rely more heavily on interdisciplinary collaboration. Additionally, it can be expected that there will be more translational studies focusing on the application of these findings to the development of effective treatments.
author2 School of Social Sciences
author_facet School of Social Sciences
Lim, Mengyu
Carollo, Alessandro
Neoh, Michelle Jin Yee
Esposito, Gianluca
format Article
author Lim, Mengyu
Carollo, Alessandro
Neoh, Michelle Jin Yee
Esposito, Gianluca
author_sort Lim, Mengyu
title Mapping miRNA research in schizophrenia: a scientometric review
title_short Mapping miRNA research in schizophrenia: a scientometric review
title_full Mapping miRNA research in schizophrenia: a scientometric review
title_fullStr Mapping miRNA research in schizophrenia: a scientometric review
title_full_unstemmed Mapping miRNA research in schizophrenia: a scientometric review
title_sort mapping mirna research in schizophrenia: a scientometric review
publishDate 2023
url https://hdl.handle.net/10356/169557
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