Machine learning in antibacterial discovery and development - A bibliometric and network analysis of research hotspots and trends

Aug 3, 2026

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This article explores the application of machine learning (ML) methods in the discovery and development of antibacterial agents. It presents a bibliometric and network analysis of research trends and hotspots in this field, utilizing Scopus data from 2006 to 2022. A sample of 1506 documents was analyzed to assess the contributions of leading authors, institutions, and countries, as well as to examine bibliometric linkages. The study employed bibliometrix R-Tool and VOSviewer software for the analysis, aiming to identify essential topics related to the application of machine learning in the discovery of new potential antibacterial drugs. The research contributes to understanding the current landscape and future directions in antibacterial drug discovery through advanced computational techniques.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

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FAQs

What is the main objective of this research?

The main objective is to conduct a bibliometric and network analysis of research hotspots and trends in machine learning for antibacterial discovery and development.

What type of data was used in the study?

The study used a sample of 1506 Scopus documents published between 2006 and 2022.

Which software was used for the analysis?

The analysis was performed using the bibliometrix R-Tool and VOSviewer software.

Aug 3, 2026

Upload by Eliana