Characterizing Highly Cited Papers in Mass Cytometry through H-Classics

Biology

Pablo Sánchez-Núñez¹  Camilla Stephens²  M.Isabel Lucena²  DanielE. Di Zeo-Sánchez² 

[1] Departamento de Comunicación Audiovisual y Publicidad, Facultad de Ciencias de la Comunicación, Universidad de Málaga, 29010 Malaga, Spain;Servicio de Farmacología Clínica, Hospital Universitario Virgen de la Victoria, Instituto de Investigación Biomédica de Málaga (IBIMA), Facultad de Medicina, Universidad de Málaga, 29010 Malaga, Spain;

关键词: mass cytometry;    cytometry by time of flight (CyTOF);    H-index;    H-classics;    highly cited papers (HCP);    bibliometric indicators;   

DOI  :  10.3390/biology10020104

来源: DOAJ

【 摘 要 】

Mass cytometry (CyTOF) is a relatively novel technique for the multiparametric analysis of single-cell features with an increasing central role in cell biology, immunology, pharmacology, and biomedicine. This technique mixes the fundamentals of flow cytometry with mass spectrometry and is mainly used for in-depth studies of the immune system and diseases with a significant immune load, such as cancer, autoimmune diseases, and viral diseases like HIV or the recently emerged COVID-19, produced by the SARS-CoV-2 coronavirus. The objective of this study was to provide a useful insight into the evolution of the mass cytometry research field, revealing the knowledge structure (conceptual and social) and authors, countries, sources, documents, and organizations that have made the most significant contribution to its development. We retrieved 937 articles from the Web of Science (2010–2019), analysed 71 Highly Cited Papers (HCP) through the H-Classics methodology and computed the data by using Bibliometrix R package. HCP sources corresponded to high-impact journals, such as Nature Biotechnology and Cell, and its production was concentrated in the US, and specifically Stanford University, affiliation of the most relevant authors in the field. HCPs analysis confirmed great interest in the study of the immune system and complex data processing in the mass cytometry research field.

【 授权许可】

Unknown