A comprehensive overview of cellular senescence from 1990 to 2021: A machine learning-based bibliometric analysis.

ABSTRACT:

Background

As a cellular process, senescence functions to prevent the proliferation of damaged, old and tumor-like cells, as well as participate in embryonic development, tissue repair, etc. This study aimed to analyze the themes and topics of the scientific publications related to cellular senescence in the past three decades by machine learning.

Methods

The MeSH term "cellular senescence" was used for searching publications from 1990 to 2021 on the PubMed database, while the R platform was adopted to obtain associated data. A topic network was constructed by latent Dirichlet allocation (LDA) and the Louvain algorithm.

Results

A total of 21,910 publications were finally recruited in this article. Basic studies (15,382, 70.21%) accounted for the most proportion of pub

SUBMITTER: Li C 

PROVIDER: S-EPMC9894629 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature