ReviewExperimental biology and medicine (Maywood, N.J.)2026
Global MyoG research 2004-2024: a bibliometric analysis of trends and translational implications.
Review in Experimental biology and medicine (Maywood, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Integrated RNA-seq and ATAC-seq analyses reveal muscle development differences between european meat pigeon and shiqi pigeon during embryonic to post-hatching stages.Frontiers in cell and developmental biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Myogenin (MyoG) is a core myogenic transcription factor that orchestrates myoblast differentiation and myofiber maturation and has been increasingly implicated in skeletal muscle degeneration and rhabdomyosarcoma, yet its global research landscape has not been systematically characterized. In this study, we performed a bibliometric analysis of MyoG-related publications from 2004 to 2024 retrieved from the Web of Science Core Collection. A total of 402 articles authored by 2,402 researchers from 1,148 institutions across 165 countries and regions were analyzed using VOSviewer, CiteSpace and R-based bibliometric tools. We quantified annual publication output, identified leading countries, institutions, authors and journals, and reconstructed collaboration, co-citation and keyword co-occurrence networks to delineate thematic evolution. The global pattern showed a multipolar structure dominated by the United States and China, with European institutions forming an additional hub and emerging countries contributing with growing but comparatively lower impact. Research hotspots exhibited a clear progression from early work on molecular mechanisms (DNA binding, MyoD family interactions, chromatin remodelling) toward regenerative biology (satellite cell regulation, muscle regeneration) and, more recently, disease-oriented studies focused on muscle atrophy, Duchenne muscular dystrophy and rhabdomyosarcoma. Landmark co-cited studies established MyoG as an indispensable regulator of skeletal muscle differentiation and highlighted its expanding relevance in pathological remodelling and therapeutic targeting. Future work is expected to concentrate on decoding MyoG-centred regulatory networks in degenerative muscle disease, integrating single-cell and spatial transcriptomics with functional genomics and multi-omics, and developing MyoG-based diagnostic and targeted therapeutic strategies. Despite the intrinsic limitations of single-database and citation-based approaches, this study provides a panoramic overview of two decades of MyoG research and offers a structured framework to guide future basic and translational investigations in muscle biology and oncology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.