Bibliometric and Text-Mining Analysis of Lipidomics and Metabolomics, 2004-2024

9,628 scientific articles on lipidomics and metabolomics in human disease were analyzed from 2004 to 2024. The dataset, created by Alejandro I. Trejo-Castro, shows the field expanded at an annual growth rate of 32.6%. It identifies leading journals, authors, countries, and emerging research themes like artificial intelligence and multi-omics integration.

Use Cases

• Analyze publication trends and growth rates based on the 20-year time series from 2004 to 2024
• Map thematic structures and keyword dynamics based on the text-mining analysis described
• Identify leading contributors and institutions based on country and author productivity rankings
• Trace methodological evolution based on mentions of techniques like liquid chromatography-mass spectrometry

Strengths

• Analysis is based on 9,628 harmonized articles, providing a substantial corpus
• Data covers a 20-year time range from 2004 to 2024
• Methodology involved cross-database validation using Scopus, Web of Science, and PubMed
• The dataset is structured as an Excel file (XLSX) with a defined size of 13.2 MB

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment for some analyses
• The dataset is relatively small at 13.2 MB, which may limit the depth of raw text data included

Provenance

Source

Scopus, with validation searches in Web of Science Core Collection and PubMed

Collection Method

Bibliometric and text-mining analysis using Bibliometrix, Scimago Graphica, OpenRefine, and custom R scripts

Time Range

2004 to 2024

Freshness

Last updated 2026-05-19 04:25:25; freshness should be verified

Geography

Global, with leading output from the United States, China, and major European contributors