Table 9_A bibliometric and text-mining analysis of lipidomics and metabolomics in human di
by Alejandro I. Trejo-Castro·Updated 19d ago
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Description
A bibliometric and text-mining analysis of 9,628 scientific articles from 2004 to 2024, sourced from Scopus and validated against Web of Science and PubMed. The study was conducted by Alejandro I. Trejo-Castro and provides an overview of the evolution of lipidomics and metabolomics in human disease research. It identifies leading journals, authors, countries, and thematic trends within the field.
Use Cases
Analyze publication trends and growth rates in lipidomics and metabolomics based on the described bibliometric indicators.
Map thematic structures and keyword dynamics in omics research based on the semantic and conceptual mapping methodology.
Identify leading journals, authors, and countries in the field based on the quantitative analysis of 9,628 articles.
Study the evolution of analytical methodologies and emerging topics like AI and multi-omics integration based on the described results.
Strengths
Analysis is based on 9,628 harmonized articles, providing a substantial corpus.
Data was validated through a multi-database comparative approach using Scopus, Web of Science, and PubMed.
The study covers a 20-year time range from 2004 to 2024, enabling longitudinal trend analysis.
The description provides specific metrics, such as an annual growth rate of 32.6%.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
The primary data file is a 1.1 MB DOCX document, which may not be a structured data format.
Provenance
Source
Scopus, with validation searches in Web of Science Core Collection and PubMed.
Collection Method
Articles were harmonized and analyzed using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts.
Time Range
2004 to 2024
Freshness
Last updated 2026-05-19 04:25:23; freshness should be verified.
Geography
Global, with leading contributions from the United States, China, and Europe.
The dataset is a 1.1 MB DOCX document; users may need to extract structured data from the report.