Bibliometric Analysis on Methods and Tools Developed for DGE Analysis: Current Trends and Future Perspectives

Necla Koçhan

Article Details

Bibliometric Analysis on Methods and Tools Developed for DGE Analysis: Current Trends and Future Perspectives

Authors:

Necla Koçhan

Publisher:

Van Yuzuncu Yıl University

Main Topics:

Biyoistatistik | İstatistiksel Analiz

Journal:

Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.30 Issue 1, pp.78-91

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001344501

pISSN:

1300-5413

Keywords:

Abstract:

 Differential gene expression DGE analysis has gained significant attention with the advent of next-generation sequencing technologies, leading to the development of a wide range of methods and tools for DGE analysis. We performed bibliometric analysis using Biblioshiny and VOSviewer software to investigate the trends over the investigated period. Relevant papers with differential gene expression related terms as the subjects from 2005 to 2023 were retrieved from the Web of Science database. Network maps were generated using Biblioshiny and VOSviewer software to illustrate the published trends over the investigated period. A total of 729 studies were examined to reveal trends in the DGE analysis methodologies, tools, and packages. In the analysis, co-authorship, bibliographic coupling, and co-occurrence analyses were conducted for country, institution, source, author, and keyword productivity. It was found that the output and citation numbers increased after 2005. During the study period, the USA and China emerged as the leading contributors to the field. The temporal study revealed a significant increase in publications at certain times, followed by period of slight decrease. The greatest fall was observed between 2008 and 2010. Despite these decreases, DGE analysis remains a critical topic in genomics due to its essential role in understanding the mechanisms of any disease, gene function, and therapeutic targets. This trend suggests that current methods and tools are considered sufficiently powerful for identifying key informative genes associated with diverse diseases.

 Differential gene expression DGE analysis has gained significant attention with the advent of next-generation sequencing technologies, leading to the development of a wide range of methods and tools for DGE analysis. We performed bibliometric analysis using Biblioshiny and VOSviewer software to investigate the trends over the investigated period. Relevant papers with differential gene expression related terms as the subjects from 2005 to 2023 were retrieved from the Web of Science database. Network maps were generated using Biblioshiny and VOSviewer software to illustrate the published trends over the investigated period. A total of 729 studies were examined to reveal trends in the DGE analysis methodologies, tools, and packages. In the analysis, co-authorship, bibliographic coupling, and co-occurrence analyses were conducted for country, institution, source, author, and keyword productivity. It was found that the output and citation numbers increased after 2005. During the study period, the USA and China emerged as the leading contributors to the field. The temporal study revealed a significant increase in publications at certain times, followed by period of slight decrease. The greatest fall was observed between 2008 and 2010. Despite these decreases, DGE analysis remains a critical topic in genomics due to its essential role in understanding the mechanisms of any disease, gene function, and therapeutic targets. This trend suggests that current methods and tools are considered sufficiently powerful for identifying key informative genes associated with diverse diseases.

 Differential gene expression DGE analysis has gained significant attention with the advent of next-generation sequencing technologies, leading to the development of a wide range of methods and tools for DGE analysis. We performed bibliometric analysis using Biblioshiny and VOSviewer software to investigate the trends over the investigated period. Relevant papers with differential gene expression related terms as the subjects from 2005 to 2023 were retrieved from the Web of Science database. Network maps were generated using Biblioshiny and VOSviewer software to illustrate the published trends over the investigated period. A total of 729 studies were examined to reveal trends in the DGE analysis methodologies, tools, and packages. In the analysis, co-authorship, bibliographic coupling, and co-occurrence analyses were conducted for country, institution, source, author, and keyword productivity. It was found that the output and citation numbers increased after 2005. During the study period, the USA and China emerged as the leading contributors to the field. The temporal study revealed a significant increase in publications at certain times, followed by period of slight decrease. The greatest fall was observed between 2008 and 2010. Despite these decreases, DGE analysis remains a critical topic in genomics due to its essential role in understanding the mechanisms of any disease, gene function, and therapeutic targets. This trend suggests that current methods and tools are considered sufficiently powerful for identifying key informative genes associated with diverse diseases.

 Diferansiyel gen ekspresyonu DGE analizi, yeni nesil dizileme teknolojilerinin ortaya çıkışıyla önemli bir ilgi kazanmıştır. Bu durum, DGE analizi için çeşitli yöntemlerin ve araçların geliştirilmesine yol açmıştır. Bu çalışmada, Biblioshiny ve VOSviewer yazılımları kullanılarak, incelenen dönem boyunca eğilimleri araştırmak amacıyla bibliyometrik analiz yapılmıştır. 2005-2023 yılları arasında Web of Science veri tabanından, diferansiyel gen ekspresyonu ile ilgili terimleri konu alan ilgili makaleler taranmıştır. İncelenen dönem boyunca yayımlanan eğilimleri göstermek için Biblioshiny ve VOSviewer yazılımları kullanılarak ağ haritaları oluşturulmuştur. Toplamda 729 çalışma, DGE analizi metodolojilerindeki, araçlarındaki ve paketlerindeki eğilimleri ortaya koymak amacıyla incelenmiştir. Bu amaçla, ülke, kurum, kaynak, yazar ve anahtar kelime üretkenliği açısından eş-yazarlık, bibliyografik eşleşme ve eş-oluşum analizleri yapılmıştır. 2005 yılından sonra çıktı ve atıf sayılarında artış gözlenmiştir. Çalışma süresince ABD ve Çin, DGE analizine en çok katkı sağlayan ülkeler olarak öne çıkmıştır. Zamansal çalışmalar, belirli aralıklarla bir miktar azalma olmakla birlikte, zaman içinde yayınlarda önemli bir artış olduğunu ortaya koymuştur. En büyük düşüş, 2008 ile 2010 yılları arasında gözlenmiştir. Bu düşüşlere rağmen, DGE analizi, herhangi bir hastalığın mekanizmalarını, gen işlevlerini ve terapötik hedefleri anlamadaki temel rolü nedeniyle genomikte kritik bir konu olmaya devam etmektedir. Bu eğilim, mevcut yöntemlerin ve araçların, çeşitli hastalıklarla ilişkili anahtar bilgilendirici genleri tanımlamak için yeterince güçlü kabul edildiğini göstermektedir.

Article Details

Bibliometric Analysis on Methods and Tools Developed for DGE Analysis: Current Trends and Future Perspectives

Authors:

Necla Koçhan

Publisher:

Van Yuzuncu Yıl University

Main Topics:

Biyoistatistik | İstatistiksel Analiz

Journal:

Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.30 Issue 1, pp.78-91

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001344501

pISSN:

1300-5413

Bibliometric analysis

Differential expression analysis

Differential gene expression

Gene expression

RNA-seqBibliyometrik analiz

Diferansiyel dizileme analizi

Diferansiyel gen ekspresyonu

Gen ifadesi

RNA-dizileme

Issues

Article Details

Authors: Necla Koçhan

Publisher: Van Yuzuncu Yıl University

Main Topics: Biyoistatistik | İstatistiksel Analiz

Journal: Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.30 Issue 1, pp.78-91

Document Type: Article

Publication Date: 4/2025

Document Language: English

Document ID (Org No.): 2001344501

pISSN: 1300-5413

Issues

Authors:

Necla Koçhan

Publisher:

Van Yuzuncu Yıl University

Main Topics:

Biyoistatistik | İstatistiksel Analiz

Journal:

Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.30 Issue 1, pp.78-91

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001344501

pISSN:

1300-5413