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  4. MAATrica: a measure for assessing consistency and methods in medicinal and nutraceutical chemistry papers
 
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2024
Journal Article
Title

MAATrica: a measure for assessing consistency and methods in medicinal and nutraceutical chemistry papers

Abstract
The growing number of scientific papers and document sources underscores the need for methods capable of evaluating the quality of publications. Researchers who are looking for relevant papers for their studies need ways to assess the scientific value of these documents. One approach involves using semantic search engines that can automatically extract important knowledge from the growing body of text. In this study, we introduce a new metric called “MAATrica,” which serves as the foundation for an innovative method designed to evaluate research papers. MAATrica offers a new way to analyze and categorize text, focusing on the consistency of research documents in the life sciences, particularly in the fields of medicinal and nutraceutical chemistry. This method utilizes semantic descriptions to cover in silico experiments, as well as in vitro and in vivo essays. Created to aid in evaluation processes like peer review, MAATrica uses toolkits and semantic applications to build the proposed measure, identify scientific entities, and gather information. We have applied MAATrica to roughly 90,000 papers and present our findings here.
Author(s)
Panzarella, Giulia
Gallo, Alessandro
Coecke, Sandra
Querci, Maddalena
Ortuso, Francesco
Hofmann-Apitius, Martin  
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Veltri, Pierangelo
Bajorath, Jürgen
Alcaro, Stefano
Journal
European journal of medicinal chemistry  
Open Access
DOI
10.1016/j.ejmech.2024.116522
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Keyword(s)
  • Information extraction

  • Medicinal chemistry

  • Nutraceuticals

  • Research metrics

  • Text mining

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